Statistical Semantics – Meta-Guide.com

Notes:

Statistical semantics is a subfield of linguistics that deals with the use of statistical techniques to analyze and understand the meanings of words and phrases. It is based on the idea that the meanings of words and phrases can be inferred from the way they are used in large corpora of text, and that statistical methods can be used to analyze these patterns of usage to extract meaning.

In statistical semantics, researchers use techniques such as frequency analysis, mutual information, and clustering to identify patterns of usage that can be used to infer meaning. For example, a word that is frequently used in conjunction with other words that have a particular meaning is likely to have a similar meaning itself. Similarly, a word that is used in a consistent pattern across different contexts is likely to have a more stable and well-defined meaning.

Statistical semantics has a wide range of applications, including information retrieval, natural language processing, machine translation, and computational linguistics. It is an important tool for understanding and analyzing the meanings of words and phrases in large corpora of text, and for building systems that can understand and process human language.

Distributional semantics refers to the study of how the meanings of words can be understood by examining the contexts in which they are used. This approach suggests that words that are used in similar contexts tend to have similar meanings.
Statistical semantic parser is a type of natural language processing tool that uses statistical techniques to analyze and understand the meaning of text.
Statistical semantic parsing is a subfield of natural language processing that focuses on using statistical methods to automatically analyze and understand the meaning of text. This can include tasks such as syntactic parsing, semantic role labeling, and other forms of natural language understanding.

Resources:

assert .. automatic statistical semantic role tagger
gensim .. topic modeling for humans
jobimtext .. open source framework for application of distributional semantics
opencube toolkit .. enables the table-based visualizations of rdf data cubes

Wikipedia:

References:

Statistical semantics: Methods and applications (2020)
Knowledge Discovery in Scientific Literature (2014)
Routledge Encyclopedia of Translation Technology (2014)

Statistical semantics: Methods and applications
S Sikström, D Garcia – 2020 – books.google.com
This book discusses the application of various statistical methods to texts, rather than numbers, in various fields in behavioral science. It proposes an approach where quantitative methods are applied to data whereas previously such data were analyzed only by …

Social psychology: Evaluations of social groups with statistical semantics
MG Sendén, S Sikström – Statistical Semantics, 2020 – Springer
Semantic analyses are potentially important, but underutilized, tools to study social psychology. This chapter focuses on how semantic analysis, using personal pronouns, can be used to study important phenomena in social psychology. Personal pronouns can be …

Introduction to Statistical Semantics
S Sikström, D Garcia – Statistical Semantics, 2020 – Springer
Human beings create meaning from the fact that concepts tend to occur together in a predictable way. When we see a dog, we also see a tail, paws, eyes, legs, fur, and etcetera. In this context, we would see an owner who goes for a walk in the park with the dog that is …

What economic growth and statistical semantics tell us about the structure of the world
WL Benzon – Available at SSRN, 2020 – papers.ssrn.com
The metaphysical structure of the world, as opposed to its physical structure, resides in the relationship between our cognitive capacities and the world itself. Because the world itself is “lumpy”, rather than “smooth”(as developed herein, but akin to “simple” vs. complex”), it is …

Statistical Semantics
S Sikström, D Garcia – Springer
When I, Sverker Sikström, took my first psychology class and got an assignment in which I and my classmates were asked to collect data, the professor told us not to ask participants for responses using their words. Use rating scales instead, he said, then you can input the …

Creating semantic representations
FÅ Nielsen, LK Hansen – Statistical Semantics, 2020 – Springer
In this chapter, we present the vector space model and some ways to further process such a representation: With feature hashing, random indexing, latent semantic analysis, non-negative matrix factorization, explicit semantic analysis and word embedding, a word or a …

Prediction and semantic trained scales: Examining the relationship between semantic responses to depression and worry and the corresponding rating scales
ONE Kjell, K Kjell, D Garcia, S Sikström – Statistical Semantics, 2020 – Springer
This chapter focuses on using the semantic representations, consisting of a number of semantic dimensions, in multiple linear regressions to predict a numerical outcome variable. We examine whether there is a statistically significant relationship between texts and …

Linguistic: Application of LSA to predict linguistic maturity and language disorder in children
K Hansson, B Sahlén, R Bååth, S Sikström – Statistical Semantics, 2020 – Springer
In this chapter we will describe applications of latent semantic analysis to assess semantic linguistic maturity in children and how well the method can predict whether a child has developmental language disorder (DLD), based on orally produced narratives. Assessment …

Software for creating and analyzing semantic representations
FÅ Nielsen, LK Hansen – Statistical Semantics, 2020 – Springer
In this chapter, we describe some of the software packages for learning distributed semantic representation in the form of word and graph embeddings. We also describe several Python natural language processing frameworks that can prepare a corpus for the embedding …

A ternary model of personality: temperament, character, and identity
D Garcia, KM Cloninger, S Sikström, H Anckarsäter… – … Semantics, 2020 – Springer
Human beings are definitely storytellers capable of travel back and forward in time. We not only construct stories about ourselves, but also share these with others (McAdams and McLean 2013). We construct and internalize an evolving and integrative story for life, that is …

Semantic Similarity Scales: Using Semantic Similarity Scales to Measure Depression and Worry
ONE Kjell, K Kjell, D Garcia, S Sikström – Statistical Semantics, 2020 – Springer
This chapter describes how semantic representations based on Latent Semantic Analysis (LSA; Landauer and Dumais 1997) may be used to measure the semantic similarity between two words, sets of words or texts. Whereas Nielsen and Hansen describe how to create semantic …

Dark identity: distinction between malevolent character traits through self-descriptive language
D Garcia, P Rosenberg, S Sikström – Statistical Semantics, 2020 – Springer
Peoples’ tendencies to be manipulative, opportunistic, selfish, callous, amoral, and self-centered (ie, an outlook of separateness; Cloninger, Feeling good: The science of well-being, Oxford University Press, 2004; Southern Medical Journal, 100, 740–743, 2007; Mens …

SemanticExcel. com: An online software for statistical analyses of text data based on natural language processing
S Sikström, ONE Kjell, K Kjell – Statistical Semantics, 2020 – Springer
The overall aim of this chapter is to present a guide in how to efficiently measure and statistically analyze text and numerical data using the online software SemanticExcel. com; we will focus on the following main functions:

The (Mis)measurement of Happiness: Words We Associate to Happiness (Semantic Memory) and Narratives of What Makes Us Happy (Episodic Memory)
D Garcia, A Al Nima, ONE Kjell, A Granjard… – … Semantics, 2020 – Springer
Happiness or subjective well-being is often measured by assessing individuals’ judgments of life satisfaction and experience of positive and negative affect (Diener, Psychological Bulletin, 95, 542–575, 1984). In addition, recent research suggests that individuals’ sense of …

Political science: Moving from numbers to words in the case of Brexit
A Fredén – Statistical Semantics, 2020 – Springer
Quantitative text analysis is a growing research field in political science, whereas very few combine survey experiments with in-depth analysis of citizens’ word expressions. This chapter illustrates how a survey experiment and a latent semantic analysis are successfully …

Neuroscience: Mapping the semantic representation of the brain
L Langensee, J Mårtensson – Statistical Semantics, 2020 – Springer
… Statistical Semantics. Download book … Among other things, Garrard et al. (2001) conclude based on their findings that living and non-living concepts do not differ significantly in terms of the ratio of features that were used to describe them—meaning that their results fail to corroborate the …

Implicit attitudes: Quantitative semantic misattribution procedure
N Lanbeck, D Garcia, C Amato, A Olsson… – Statistical Semantics, 2020 – Springer
Certain mental processes are suggested to exist beyond conscious awareness and control. These processes have often been categorized as implicit, in contrast to explicit, processes, which are readily available to conscious report. Researchers have attempted to measure …

Space: The importance of language as an index of psychosocial states in future space missions
SM Schmer-Galunder – Statistical Semantics, 2020 – Springer
A recent article in the New England Journal of Medicine with the title “Cursed by Knowledge—Building a Culture of Psychological Safety” describes how high quality teams (with good relationships and supportive, available leadership) have higher error rates than low quality …

Compositional Generalization via Semantic Tagging
H Zheng, M Lapata – arXiv preprint arXiv:2010.11818, 2020 – arxiv.org
Page 1. Compositional Generalization via Semantic Tagging Hao Zheng and Mirella Lapata Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB Hao.Zheng@ed.ac.uk mlap@inf.ed.ac.uk …

SIGCHI Lifetime Research Award Talk: Interdisciplinary Perspectives on Search
ST Dumais – Extended Abstracts of the 2020 CHI Conference on …, 2020 – dl.acm.org
… This fundamental characteristic of human language set limits on how well simple word- matching techniques can do in satisfying information needs. In a paper at the pre-CHI Gaithersburg conference in 1982 [6] we describe this problem as statistical semantics …

The Impact of Using Functional Strength Exercises on Developing the Performance Level of Skill, FLOB 360, on a Pommel Horse Under the Age of 13.
SGA Almullah – jassalexu.journals.ekb.eg
… variables groups No. N statistical semantics of the Description Arithmetic mean median Standard deviation Coefficient of skewness … Statistical semantics variables discriminant group 5=N Non-discriminant group 5=N difference between two means Value (t) validity coefficient …

Symbolic and Statistical Theories of Cognition: Towards Integrated Artificial Intelligence
Y Maruyama – International Conference on Software Engineering and …, 2020 – Springer
… The Vector Space Model of Meaning is statistical semantics of natural language, and based upon what is called the Distributional Hypothesis [54]: “words in similar contexts have similar meanings.” This is some sort of semantic contextualism, and semantic contextualism is a …

Olfactory-colour crossmodal correspondences in art, science, and design
C Spence – Cognitive Research: Principles and Implications, 2020 – Springer
… acquisition. Over the years, several different explanations have been put forward by researchers for the existence of crossmodal correspondences, including the statistical, semantic, structural, and emotional-mediation accounts …

Approximate matching-based unsupervised document indexing approach: application to biomedical domain
K Boukhari, MN Omri – Scientometrics, 2020 – Springer
… experts and save a lot of time. Indeed, indexing approaches use various methods of automatic information treatment, such as statistical, semantic, probabilistic and possibilistic methods. These approaches go through the same …

Weighting power by preference eliminates gender differences
S Sikström, LM Stoinski, K Karlsson, L Stille… – Plos one, 2020 – journals.plos.org
… most people. Two studies were conducted that used both self-rated power and statistical semantics to explore the concept of PWP. The semantic … by Sikström. Study 1: Measuring and describing power with statistical semantics. Study 1 …

A video coverless information hiding algorithm based on semantic segmentation
N Pan, J Qin, Y Tan, X Xiang… – … on Image and …, 2020 – jivp-eurasipjournals.springeropen …
Due to the fact that coverless information hiding can effectively resist the detection of steganalysis tools, it has attracted more attention in the field of information hiding. At present, most coverless information hiding schemes select text and image as transmission carriers, while there …

Object-based attention for spatio-temporal reasoning: Outperforming neuro-symbolic models with flexible distributed architectures
D Ding, F Hill, A Santoro, M Botvinick – arXiv preprint arXiv:2012.08508, 2020 – arxiv.org
… NS-DR leverages various independently-learned modules: a neural network ‘perceptual’ front-end to detect objects, a dynamics module to infer to the behaviour of objects over time, and a symbolic statistical semantic parser to represent the questions …

What are the ingredients for food systems change towards sustainability?—Insights from the literature
H Weber, K Poeggel, H Eakin, D Fischer… – Environmental …, 2020 – iopscience.iop.org
… How do the identified clusters conceptualize deep change processes towards sustainability in food systems? We analyzed 209 peer-reviewed articles using a two-step approach starting with a statistical semantic full-text analysis to group the literature into clusters …

DL-VSM based document indexing approach for information retrieval
K Boukhari, MN Omri – Journal of Ambient Intelligence and Humanized …, 2020 – Springer
… experts and save a lot of time. Indeed, indexing approaches use various methods of auto- matic information treatment, such as statistical, semantic, probabilistic and possibilistic methods. These approaches go through the same …

Automatic domain modeling for human–robot interaction
SŽ Savi?, M Gnjatovi?, D Stefanovi?, B Lali?… – Intelligent Service …, 2020 – Springer
… groups: statistical and symbolic. (i) Statistical memory models: A subgroup of statistical models that is of interest to this discussion includes distributional models related to what is known as statistical semantics. These models are …

Processing ambiguities in attachment and pronominal reference
M Grant, S Sloggett, B Dillon – Glossa: a journal of general …, 2020 – glossa-journal.org
… decisions. In response to the results challenging the syntax-first model, models under which multiple constraints from several information sources (eg, statistical, semantic, contextual) are simultaneously applied gained favour …

Optimized Transformer Models for FAQ Answering
S Damani, KN Narahari, A Chatterjee, M Gupta… – Pacific-Asia Conference …, 2020 – Springer
… Previous work on answering a question given FAQ pages (FAQ-Finder [8], Auto-FAQ [28], [2, 11, 13, 21, 23]) was based on traditional feature engineering for surfacing statistical/semantic similarities between query and questions …

A mathematical model for universal semantics
E Weinan, Y Zhou – IEEE Transactions on Pattern Analysis and …, 2020 – ieeexplore.ieee.org
… This in turn, will provide us with quantitative criteria for inclusion/exclusion of different concepts within the same (computationally constructed) semantic field. Such statistical semantic mining will then pave the way for ma- chine comprehension and machine translation …

Artificial Intelligence for Understanding Large and Complex Datacenters
P Zheng – 2020 – dukespace.lib.duke.edu
… fective interpretation. We present Limelight + , an algorithmic framework based on graph theory and statistical semantic learning, to extract workload insights from datacenter-scale stack traces, and to gain design insights for datacenter architecture. v Page 6 …

GQM-based Tree Model for Automatic Recommendation of Design Pattern Category
CK Youssef, FM Ahmed, HM Hashem… – Proceedings of the …, 2020 – dl.acm.org
… [14] Radim Rehurek and Petr Sojka. Gensim—statistical semantics in python. statistical semantics; gensim; Python; LDA; SVD, 2011. [15] Sahar Sohangir and Dingding Wang. Improved sqrt-cosine similarity measurement. Journal of Big Data, 4:25, 12 2017 …

A study on agent-based web searching and information retrieval
U Mitra, G Srivastava – Intelligent Communication, Control and Devices, 2020 – Springer
… search results. This is accomplished by the use of intelligent agents [3], specifically personal assistants. Three major information retrieval paradigms currently in use are statistical, semantic and contextual. Statistical information …

Structure of communities in semantic networks of biomedical research on disparities in health and sexism
LS Rivera-Romano, G Juárez-Cano… – Biomedica: revista del …, 2020 – europepmc.org
… However, there is still a gap between the medical and social factors that give rise to possible disparities by sex. Keywords: Biomedical research, quality of health care, health status disparities, sexism, data mining, data interpretation, statistical, semantic web …

A Graph Based Approach to Automate Essay Evaluation
R Bhatt, M Patel, G Srivastava… – 2020 IEEE International …, 2020 – ieeexplore.ieee.org
… As seen in Fig. 1, the main features extracted are based on statistical, semantic and syntactic analysis. These features were tested on different supervised prediction models to find out which model works the best. Figure 1: Extracted features …

A Text Mining Approach to Extract and Rank Innovation Insights from Research Projects
FM Malloci, LP Penadés, L Boratto, G Fenu – International Conference on …, 2020 – Springer
… The former is mapped to a preferential strength measure, while the latter is used to identify the relevant goal, through a statistical semantic similarity. Related work on topic and keyword extraction was also conducted. Aras et al …

Artificial Intelligence Frontiers in Statistics: Al and Statistics III
DJ Hand – 2020 – books.google.com
… Contents vii 295 22 Probabilistic text understanding RP Goldman and E. Charniak 23 The application of machine learning techniques in subject classification I. Kavanagh, C. Ward and J. Dunnion 312 PART SIX Other areas 325 327 24 A statistical semantics for causation J …

Conceptual Semantic Analysis of Patents and Scientific Publications Based on TRIZ Tools
V Kaliteevskii, A Deder, N Peric… – International TRIZ Future …, 2020 – Springer
… Blei, DM, Ng, AY, Jordan, MI: Latent dirichlet allocation. J. Mach. Learn. Res., 3, 993–1022 (2003)Google Scholar. 24. ?eh??ek, R., Sojka, P.: Gensim – statistical semantics in python. statistical semantics; gensim; Python; LDA; SVD (2011)Google Scholar. 25 …

Measure of filtering quality assessment of image noise using nonparametric statistic
PY Kostenko, VV Slobodyanyuk, KS Vasiuta… – Radioelectronics and …, 2020 – Springer
… image quality assessment. The processing quality of noisy original image can be considered as a characteristic of the proper image and determined by its eigenproperties: statistical, semantic, and structural. The corresponding …

Detecting Paraphrases in Marathi Language
S Srivastava, S Govilkar – International Journal, 2020 – bohrpub.com
… sentences. Keywords: Paraphrase, Marathi Language Statistical, Semantic, Sumo metric, Universal Networking Language (UNL). 1 Introduction Paraphrase is the translation of a sentence or a para- graph into same language …

Method for Encoding Video Frame Fragments Based on Non-Equilibrium Codes with Minimization of Service Data
? ??????, ? ????????, ? ??????????… – … Workshop on Cyber …, 2020 – er.chdtu.edu.ua
… ( R(t) 4 3 2 1 ? ? ? ? ? = (1) where ? is the functional, describing the relationship between the frame bit intensity and the factors affecting its value; 1 ? are sets of patterns, respectively, defining statistical, semantic and psycho-visual features of the frame; …

SEMANTIC PROPERTIES OF THE NOMINAL PARTS OF SPEECH IN THE LYRICS OF THE 2000s BRITISH INDEPENDENT SCENE
M Sterlikova – Scientific Journal of Polonia University, 2020 – pnap.ap.edu.pl
… Semantic classes are obtained by averaging at least three methods: structural, psycholinguistic, and statistical. Semantic subclasses, in contrast, require the appli- cation of logical-deductive, linguistic-inductive, and psychological-inductive methods …

A Review on Semantic Role Labeling
RR Chouhan, ZB Vaishnav – junikhyat.com
… meta-classifier that merges a set of classifiers and then classifies a new data points by taking majority vote of their predictions. In [4], the authors have introduced a statistical semantic role labeler based on supervised machine learning approach for Hindi and Urdu languages …

Exploring changes in coastal environment policy using text mining: A case study in South Korea
NW Cho, MJ Lee – Journal of Coastal Research, 2020 – meridian.allenpress.com
… The data presented in the text documents must be quantitatively converted so that the data on terms of agreement can be analyzed. The process of collecting data from text documents was based on the statistical semantics hypothesis defined by Turney and Pantel (2010) …

Breast cancer detection in mammogram image with segmentation of tumour region
VA Chinnasamy… – International Journal of …, 2020 – inderscienceonline.com
… Feature extraction ? Statistical ? Semantic Identify malignant or benign FMMNN-GWO Page 7 … The tissues are segmented by Histon based improved fuzzy C means clustering algorithm. Features such as Statistical, Semantic, etc are extracted from the segmented regions …

Solid Waste Pollution of Beaches in the Eastern Region of Benghazi City
DES Ahmed – EC Microbiology, 2020 – wherenot.com
… Table 9 shows the results of the variance test in the division of the three squares (A, B, and C). The statistical semantic test (0.109) was greater than the moral level (0.05), suggesting that there are no significant differences in the division of the three squares, as shown in the …

Research of the LDA algorithm processing results on high-level classes of patents
A Kravets, V Gneushev, S Biryukov, D Skorikov… – Intellectual …, 2020 – ceur-ws.org
… the comparison of TF * IDF vectors [11]. The unique statistical-semantic method developed in our previous research [12] significantly (by 23-25%) increases recall and precision. Another imperfection in the process of analyzing …

Machine Translation, a Game-Changer for the Language Industry
G Bulgaru – Revue Internationale d’Études en Langues Modernes …, 2020 – ceeol.com
… material. He therefore proposed directions of research suggesting methods that referred to meaning and context, language and underlying logic, translation, cryptography and statistical semantic, language and invariants. Bearing …

On the evaluation of retrofitting for supervised short-text classification
K Ghazi, A Tchechmedjiev, S Harispe… – … Deep Learning meets …, 2020 – hal.mines-ales.fr
… of the distributional hypothesis stating that words occur- ring in similar contexts tend to be semantically close [7]. This hypothesis, made popular through Firth’s idea (1957) [8]: “You shall know a word by the company it keeps”, is one of the main tenets of statistical semantics …

Interactive Natural Language Grounding via Referring Expression Comprehension and Scene Graph Parsing
J Mi, J Lyu, S Tang, Q Li, J Zhang – Frontiers in Neurorobotics, 2020 – ncbi.nlm.nih.gov
… approach. Katsumata et al. (2019) introduced a statistical semantic mapping method that enables the robot to connect multiple words embedded in spoken utterance to a place in a semantic mapping processing. However, these …

The Image of Khabarovsk Territory in the Electronic Version of the Newspaper “Tikhookeanskaya Zvezda”
AI Avdeyenko, IV Krisanova… – … Conference” Far East …, 2020 – atlantis-press.com
… selected texts published in the Internet version of «TihookeanskayaZvezda» newspaper for 2014-2018 with a total volume of language material of 2,671 sentences 50,969 words.This array was indexed using NextAnalist 2.0, a program designed for statistical semantic analysis …

Istraživanje primjene korisni?kih oznaka u predmetnom opisu gra?e: društveno ozna?avanje
A Ibri?i? – Bosniaca, 2020 – ceeol.com
… kao material. The aim of the research is to examine the application of bookmarks assigned by users, ie user bookmarks of social bookmarking in the sub- ject cataloguing, through statistical, semantic, and linguistic analysis. All …

Transformer Models for Recommending Related Questions in Web Search
R Mitra, M Gupta, S Dandapat – Proceedings of the 29th ACM …, 2020 – dl.acm.org
… Previous work on answering a question given FAQ pages or a database of QA pairs (FAQ-Finder [9], Auto-FAQ [28], [15, 24, 25]) was based on traditional feature engineering for surfacing statistical/semantic similarities between query and questions …

1. Engines of Order
B Rieder – Engines of Order, 2020 – degruyter.com
… The statistical framing of information on level A finds its equivalence in ‘statistical semantic characteristics’ on level B, and the ‘engineering noise’ that troubles Shannon’s technical transmissions becomes ‘semantic noise’ (p. 26) …

Combining Text Analysis and Concept Mapping for Conceptual Model Development
K Hanson – 2020 – shareok.org
… automatically and is user friendly while also being highly efficient (?eh??ek, 2011). The statistical semantics hypothesis states that “statistical patterns of human word usage can be used to figure out what people mean” (Turney & Pantel, 2010, p. 146) …

Cybersecurity text data classification and optimization for cti systems
A Rodriguez, K Okamura – Workshops of the International Conference on …, 2020 – Springer
… Rehurek, R., Sojka, P.: Gensim—statistical semantics in python. Statistical semantics; gensim; Python; LDA; SVD (2011)Google Scholar. Copyright information. © Springer Nature Switzerland AG 2020. Authors and Affiliations …

Research on Deep Learning Based Topic Representation of Hot Events
Y Chuanming, Y Sai, Z Xingyu… – Data Analysis and …, 2020 – manu44.magtech.com.cn
… ?????????????????? 2.2 ??????????????? ???????????????????? ????Statistical Semantic Models??????? ???Embedded Vectors Models??11???? ?1???????????????????? …

4chan & 8chan embeddings
P Voué, T De Smedt, G De Pauw – arXiv preprint arXiv:2005.06946, 2020 – arxiv.org
… Online misogyny, harassment and hate crimes. In Sexual violence in a digital age (pp. 153-193). Palgrave Macmillan, London. ?eh??ek, R., & Sojka, P. (2011). Gensim – statistical semantics in python. Retrieved from https://gensim.org. Shultz, A. (2019) …

A Hybrid BERT and LightGBM based Model for Predicting Emotion GIF Categories on Twitter
Y Bi, S Wang, Z Fan – arXiv preprint arXiv:2008.06176, 2020 – arxiv.org
… negative samples. For the Page 3. LightGBM BERT Feature Engineering Statistical Semantic Features Text Reply Similarity Related Features Pointwise Learning Pairwise Learning Figure 1: The Model Overview. Model Offline …

A comparative analysis of searching algorithms
AA Alsalmi – Journal of University Studies for inclusive Research, 2020 – usrij.com
… Page 5. 5 4. How to improve data validation system? Lexicon is statistical, semantics is universal A semantic idea or semantics describes the structure of meaning. The relation between expressions and meanings as well as among the expressions themselves is a site of lexical …

Machine learning for ambulatory applications of neuropsychological testing
C Chandler, PW Foltz, AS Cohen, TB Holmlund… – Intelligence-Based …, 2020 – Elsevier
… Thus, we utilized the latest in speech technologies so as to automatically analyze audio properties and recognize speech output (ie, via an automated speech recognition system) and then perform statistical semantic and syntactic analyses of language …

An analysis of YouTube comments on BTS using text mining
HOK KO – 2020 – ther3journal.com
… and to identify the contexts of those words. Text mining is based on the “statistical semantic hypothesis,” which states that it is possible to extract meaningful information from text data. This hypothesis posits that “the intentions of …

Chichang Jou
MY Day – 2020 – mail.tku.edu.tw
Page 1. (Text Mining) 1 1082TM01 MBA, BDABI, TKU (E3611) (8480) (Spring 2020) Mon, 7, 8, 9 (14:10-17:00) (B206) (Course Orientation on Text Mining) …

Artificial Intelligence for Text Analytics
MY Day – 2020 – ntpu.edu.tw
Page 1. (AI for Text Analytics) 1 (Course Orientation on Artificial Intelligence for Text Analytics) Tamkang Universit y 1091AITA01 MBA, IMTKU (M2455) (8418) (Fall 2020) Thu 3, 4 (10:10-12:00) (B206) Min-Yuh Day Associate Professor …

Mapping Topic Evolution Across Poetic Traditions
P Plechac, TN Haider – arXiv preprint arXiv:2006.15732, 2020 – arxiv.org
… Frontiers in Digital Humanities, 5:15. Page 7. Radim Rehurek and Petr Sojka. 2011. Gensim—statistical semantics in python. statistical seman- tics; gensim; Python; LDA; SVD. Helmut Schmid. 1994. Probabilistic part-of-speech tagging using decision trees …

Complex network based supervised keyword extractor
S Duari, V Bhatnagar – Expert Systems with Applications, 2020 – Elsevier
… author intends to communicate. The interaction between words can be mapped using various relationships, such as statistical, semantic, syntactic, discourse, cognitive, etc. (Blanco & Lioma, 2012). The most frequently used …

Word Embedding for the Historian: Employing LSI to Understand How Words Were Historically Used
L Baer-Tsarfati – CSDH-SCHN 2020, 2020 – hcommons.org
… Notes) 7 [SLIDE 7 / SEMANTIC TEXT ANALYSIS] • Computational analysis drawn from research in the field of lexical statistical semantics, also known as vector space modelling, word space modelling, or word embedding. • Uses …

What are the ingredients for food systems change towards sustainability?—Insights from the literature
L Klerkx, S Begemann – fox.leuphana.de
… How do the identified clusters conceptualize deep change processes towards sustainability in food sys- tems? We analyzed 209 peer-reviewed articles using a two-step approach starting with a statistical semantic full-text analysis to group the literature into clusters …

Machine Learning Vs Lexicon-based Approach for Sentiment Analysis in SNS
MPD Kaware, AB Raut – Journal of Seybold Report ISSN NO – seyboldjournal.com
… Corpus-based strategies are: • Statistical • Semantic • Statistical In case the word shows up intermittently amid positive texts, at that point its polarity is positive. If it much of the time shows up among negative writings, at that point its extremity can be considered as negative …

SENTIMENT ANALYSIS IN HEALTHCARE: MOTIVES, CHALLENGES & OPPORTUNITIES PERTAINING TO MACHINE LEARNING
ST Lai, R Mafas – International Journal of Management (IJM), 2020 – researchgate.net
Page 1. http://www.iaeme.com/IJM/index.asp 1166 editor@iaeme.com International Journal of Management (IJM) Volume 11, Issue 11, November 2020, pp. 1166-1174. Article ID: IJM_11_11_109 Available online at http://www …

A Working Well-Being: The Individual’s Relation to Their Job Relates to Their Well-Being
L Mårtensson, S Dolovski – 2020 – lup.lub.lu.se
… semantic content (Kjell et al., 2016). The statistical semantics analyses of these words revealed that satisfaction relates to words such as ?money?, ?job, success, wealth, achievement etc … how a set of items are related. Statistical semantics was used in this study to quantify the …

Corrigendum to Improve Language Modelling for Code Completion through Learning General Token Repetition of Source Code
Y Yang – arXiv preprint arXiv:2005.04137, 2020 – arxiv.org
… [Online]. Available: http://dx.doi.org/10.1109/MSR.2013.6624029 [7] TT Nguyen, AT Nguyen, HA Nguyen, and TN Nguyen, “A statistical semantic language model for source code,” in ESEC/FSE’13, Saint Petersburg, Russian Federation, August 18-26, 2013, 2013, pp. 532–542 …

Computationally analyzing social media text for topics: A primer for advertising researchers
JT Yun, BRL Duff, PT Vargas, H Sundaram… – Journal of Interactive …, 2020 – Taylor & Francis
Advertising researchers and practitioners are increasingly using social media analytics (SMA), but focused overviews that explain how to use various SMA techniques are scarce. We focus on how resea…

Research on Visual Relation Detection Based on Computer Vision
M Liu, H Wang, Y Li, Y Bian – 2020 3rd International …, 2020 – ieeexplore.ieee.org
… model for linN prediction [13]. They showed how the combination of a statistical semantic model and a visual model could improve the tasN of mapping pictures to their related scene descriptions. They have applied a variety …

Validation of subjective well-being measures using item response theory
AA Nima, KM Cloninger, BN Persson… – Frontiers in …, 2020 – frontiersin.org
Background: Subjective well-being refers to the extent to which a person believes or feels that her life is going well. It is considered as one of the best available proxies for a broader, more canonical form of well-being. For over 30 years, one important distinction in the conceptualization …

A checklist for choosing between R packages in ecology and evolution
CJ Lortie, J Braun, A Filazzola… – Ecology and …, 2020 – Wiley Online Library
… Statistical semantics is a formal term (Rekabsaz, Bierig, Ionescu, Hanbury, & Lupu, 2015), but here, we use the concept of semantics more broadly to describe the meaning of the terms employed to label functions and statistical tasks (Soyer, 2017) …

Forecasting News Events Using the Theory of Self-similarity by Analysing the Spectra of Information Processes Derived from the Vector Representation of Text …
K Otradnov – … , Convergent 2018, Moscow, Russia, November 29 …, 2020 – books.google.com
… 3 The Model for Forecasting News Events Based on Information Process Spectrums Analysis with the Hurst Self Similarity Method 3.1 Extracting Spectrums of Information News Processes from Text Documents Statistical semantic hypothesis allows us to formalize text document …

Research and Application of Machine Learning in Automatic Program Generation
X Zhang, Y Jiang – Chinese Journal of Electronics, 2020 – IET
… In order to improve predictability, Nguyen TT et al.[12] introduced a novel statistical semantic language model source code model SLAMC (A novel statistical Semantic language model for source code), which combined semantic information into code tokens and simulates the …

Different valuable tools for Arabic sentiment analysis: a comparative evaluation.
Y Zahidi, Y El Younoussi… – International Journal of … – pdfs.semanticscholar.org
… developed in the package. It supports three main NLP modern tasks: retrieve semantically similar documents, scalable statistical semantics, and analyze plain-text documents for semantic structure [18]. Gensim includes streamed …

Audio–Video Aid Generator for Multisensory Learning
RK Sharma, AA Bora, S Bhaskar, P Kumar – International Conference on …, 2020 – Springer
… 4 (2012)Google Scholar. 15. R. ?eh??ek, P. Sojka, Gensim statistical semantics in python (2011)Google Scholar. 16. A. Joulin, E. Grave, P. Bojanowski, T. Mikolov, Bag of tricks for efficient text classificationGoogle Scholar. 17 …

Verification of the Factors of Quality Image Formation in Advanced Companies with Emotional Value
K Takumi, K TSUDA – International Journal of New Technology and Research – neliti.com
… understand spoken words, it is roughly divided into rule base and statistical meaning understanding. Tsuchiya judges emotions according to the rule of 8,024[12]. Harada uses statistical semantic understanding of, for example, LDA to understand spoken words[13] …

Analysis the Issue of Increasing National Health Insurance (BPJS Kesehatan) Rates through Community Perspectives on Social Media: A Case Study of Drone Emprit
MA Laagu, AS Arifin – 2020 International Conference on Smart …, 2020 – ieeexplore.ieee.org
… Bayesian Network Maximum Entropy Dictionary Based Approach Corpus Based Approach Statistical Semantic 2020 International Conference on Smart Technology and Applications (ICoSTA) Page 5. Fig 8. Total mention related to the issue of increase BPJS Kesehatan fees …

Soft Computing and Signal Processing: Proceedings of 2nd ICSCSP 2019
VS Reddy, VK Prasad, J Wang, KTV Reddy – 2020 – books.google.com
… Card Fraud Detection….. 125 Pranali Shenvi, Neel Samant, Shubham Kumar and Vaishali Kulkarni A Statistical-Semantic PSO Model for Customer Reviews-Based Question Answering Systems….. 137 Garima …

Quantum physics and cognitive science from a Wittgensteinian perspective: Bohr’s classicism, Chomsky’s universalism, and Bell’s contextualism
Y Maruyama – Wittgensteinian (adj.), 2020 – Springer
… The Wittgenstein’s earlier conception of meaning as correspondence with reality is now standard in logical semantics. The Wittgenstein’s later conception of meaning as use in linguistic context is actually standard in statistical semantics …

Question Answering Systems on Holy Quran: A Review of Existing Frameworks, Approaches, Algorithms and Research Issues
FS Utomo, N Suryana, MS Azmi – Journal of Physics: Conference …, 2020 – iopscience.iop.org
… Approaches Used for Question Answering Systems Development on Holy Quran Generally, there are five approaches to perform question analysis, document processing, and answer extraction inside the QAS, ie, linguistic, statistical, semantic, rule-based pattern matching, and …

A Method for the Assisted Translation of QA Datasets Using Multilingual Sentence Embeddings
T Vakili – 2020 – diva-portal.org
… This view fits a computational approach well and is a foundational idea of statistical semantics. Returning to the bag-of-words approach mentioned in the previous section, let us consider the following example to illustrate why this is useful …

Learning word hierarchical representations with neural networks for document modeling
L Wang, Y Wang, Y Xie – Journal of Experimental & Theoretical …, 2020 – Taylor & Francis
Word embedding models treat words with equal status, which leads to the neglect of hierarchical semantic relationships between words (eg, ‘green’ – ‘color’ and ‘cat’ – ‘mammal’). To build a hiera…

Transys: Leveraging Common Security Properties Across Hardware Designs
R Zhang, C Sturton – 2020 IEEE Symposium on Security and …, 2020 – ieeexplore.ieee.org
… We first find the matching code windows of the two designs to narrow the scope of variables to map. We then extract statistical, semantic, and structural features of each variable, Variable Mapping Pass Structural Transformation Pass Constraint Refinement Pass Po = Ao -> Bo …

Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing
S Sadegh, J Matschinske, DB Blumenthal… – Nature …, 2020 – nature.com
Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Various studies exist about the molecular mechanisms of viral infection. However, such information is spread across many publications and it is very time-consuming to integrate, and …

Exploiting Twitter for Informativeness Classification in Disaster Situations
D Graf, W Retschitzegger, W Schwinger, B Pröll… – Transactions on Large …, 2020 – Springer
Disaster management urgently requires mechanisms for achieving situation awareness (SA) in a timely manner, allowing authorities to react in an appropriate way to reduce the impact on affected people…

GUL. LE. VER@ GhigliottinAI: A Glove based Artificial Player to Solve the Language Game “La Ghigliottina”
N De Francesco – 2020 – ceur-ws.org
… Proceed- ings of the Second Workshop on the LLVM Com- piler Infrastructure in HPC. 2015. ?Rehurek, Radim, and Petr Sojka. Gensim—statistical semantics in python. Retrieved from genism. org (2011). Loper, Edward, and Steven Bird. NLTK: the natural language toolkit …

Amorphous Region Context Modeling for Scene Recognition
H Zeng, X Song, G Chen, S Jiang – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
… We count the area of each semantic category (segmentation output labels) in the scene categories, and obtain the statistical semantic category distribution of each scene category (StatisticsDict[c] Page 5. 1520-9210 (c) 2020 IEEE …

Behavior-Based Customer Demography Prediction in E-Commerce
V Urbancokova, M Kompan, Z Trebulova… – Journal of Electronic …, 2020 – jecr.org
… The problem of short-text documents was also explored by Seifzadeh et al. [Seifzadeh et al. 2015], where the statistical semantic approach was proposed. Feature engineering was a major research question in [Aljaber et al …

Quality-related English text classification based on recurrent neural network
C Liu, X Wang – Journal of Visual Communication and Image …, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Identifying and Processing Crisis Information from Social Media
P Khare – 2020 – oro.open.ac.uk
… 68 3 Classifying Crisis Data – A Hybrid Statistical Semantic Approach 74 …

Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach
O Palagin, V Velychko, K Malakhov… – arXiv preprint arXiv …, 2020 – arxiv.org
… development [32] (which comprises three related components: learning, population and refinement) despite the fundamental differences between the ontology-related approach and distributional semantic modeling techniques (that relies on top of the statistical semantics) …

Reconceptualizing Physical Sex as a Continuum: Are There Sex Differences in Video Game Preference?
C Lonergan, R Weber – Mass Communication and Society, 2020 – Taylor & Francis
… Importantly, equivalence testing is not merely a game of statistical semantics, that is, a different way of saying what an insignificant statistical effect test would find (ie, when a classical hypothesis test reveals insignificant results, such as a t-test revealing a high p-value of 0.9) …

Hifacegan: Face renovation via collaborative suppression and replenishment
L Yang, S Wang, S Ma, W Gao, C Liu, P Wang… – Proceedings of the 28th …, 2020 – dl.acm.org
… (Up arrow means the higher score is preferred, and vice versa.) Statistical Semantic Perceptual Task Methods PSNR ? SSIM ? MS-SSIM ? FED ? LLE ? FID ? LPIPS ? NIQE ? EDSR [34] 30.188 0.824 0.961 0.0843 2.003 20.605 0.2475 13.636 …

Co-LSTM: Convolutional LSTM model for sentiment analysis in social big data
RK Behera, M Jena, SK Rath, S Misra – Information Processing & Management – Elsevier
… et al., 2011). Co-occurrence patterns of words in the text are used to evaluate the semantics in the case of contextual semantics, which is also known as statistical semantics (Turney & Pantel, 2010). External semantic knowledge …

Speech to speech interaction system using Multimedia Tools and Partially Observable Markov Decision Process for visually impaired students
S Lokesh, B Kanisha, S Nalini, MR Devi… – Multimedia Tools and …, 2020 – Springer
In general, visually impaired students need of another person’s to teach them with the help of computers and book. However, a number of students are.

Exploiting Twitter for Informativeness Classification in Disaster Situations
E Kapsammer – Transactions on Large-Scale Data-and …, 2020 – books.google.com
Page 40. Exploiting Twitter for Informativeness Classification in Disaster Situations David Graf1 (B), Werner Retschitzegger1, Wieland Schwinger1, Birgit Pröll2, and Elisabeth Kapsammer1 1 Institute of Telecooperation, Department …

Leverage label and word embedding for semantic sparse web service discovery
C Sun, L Lv, G Tian, Q Wang, X Zhang… – Mathematical Problems in …, 2020 – hindawi.com
Information retrieval-based Web service discovery approach suffers from the semantic sparsity problem caused by lacking of statistical information when the Web services are described in short texts. To handle this problem, external information is often utilized to improve the discovery …

The OpenCitations data model
M Daquino, S Peroni, D Shotton, G Colavizza… – International Semantic …, 2020 – Springer
… which is correspondingly expanded. As a result, OCO will remain a comprehensive reference point for future developments. Other statistical semantic approaches will be evaluated in the future. Secondly, we evaluated OCO …

Multi-Task Topic Analysis Framework for Hallmarks of Cancer with Weak Supervision
E Batbaatar, VH Pham, KH Ryu – Applied Sciences, 2020 – mdpi.com
The hallmarks of cancer represent an essential concept for discovering novel knowledge about cancer and for extracting the complexity of cancer. Due to the lack of topic analysis frameworks optimized specifically for cancer data, the studies on topic modeling in cancer research …

Scientific Literature Information Extraction Using Text Mining Techniques for Human Health Risk Assessment of Electromagnetic Fields
SW Lee, JH Kwon, B Lee, EJ Kim – Sensors and Materials, 2020 – myukk.org
… 19 (2019) 57. https://doi.org/10.1186/s12859-019-2607-x 11 E. Loper and S. Bird: Proc. COLING/ACL on Interactive presentation sessions (ACL, 2006) 69. 12 Gensim-statistical semantics in python: https://radimrehurek.com/gensim/ (accessed May 2019).

Design and development of a model for sentiment analysis with special reference to user feedback on public transport services
S Singh – 2020 – shodhgangotri.inflibnet.ac.in
Page 1. 1 RESEARCH PLAN PROPOSAL Design and Development of a model for Sentiment Analysis: with special reference to user feedback on public transport services. For registration to the degree of Doctor of Philosophy IN THE FACULTY OF SCIENCE …

Code Prediction Based on Graph Embedding Model
K Yang, H Yu, G Fan, X Yang, L Chen – International Conference on …, 2020 – Springer
… code and naturalness. ACM Comput. Surv. 51(4), 81:1–81:37 (2018)CrossRefGoogle Scholar. 2. Nguyen, TT, Nguyen, AT, Nguyen, HA, Nguyen, TN: A statistical semantic language model for source code. In: Joint Meeting of …

Natural language processing with machine learning to predict outcomes after ovarian cancer surgery
EL Barber, R Garg, C Persenaire, M Simon – Gynecologic oncology, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Gen2Vec: Deep Learning based Distributed Representation Framework of Words and Documents for Diagnostic Services of Power Generation Facility
MH Hwang, IT Lee, CH Chae… – The Transactions of the …, 2020 – researchgate.net
… 133-136, 2014. [18] R. Rehurek and P. Sojka, “Gensim – Statistical semantics in Python,” The 4th European Meeting on Python in Science, 2011. Page 8. The Transactions of the Korean Institute of Electrical Engineers, vol. 69, no. 12, December, pp. 1808~1815, 2020 1815 KIEE …

On-the-Fly Adaptation of Source Code Models
D Shrivastava, H Larochelle, D Tarlow – openreview.net
… In INTERSPEECH, pp. 1045–1048, 2010. Nguyen, TT, Nguyen, AT, Nguyen, HA, and Nguyen, TN A statistical semantic language model for source code. In Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering, pp. 532–542. ACM, 2013 …

Assessing Short Answers in Indonesian Using Semantic Text Similarity Method and Dynamic Corpus
U Hasanah, BP Hartato – 2020 12th International Conference …, 2020 – ieeexplore.ieee.org
… Electrical Engineering, ICITISEE 2018, 2018. [12] R. ?eh??ek and P. Sojka, “Gensim — Statistical Semantics in Python,” NLP Centre, Fac. Informatics, Masaryk Univ. Brno, Czech Repub., vol. 3, no. 2, 2011. [13] A. Islam and …

The popularity of eating broadcast: Content analysis of “mukbang” YouTube videos, media coverage, and the health impact of “mukbang” on public
EK Kang, J Lee, KH Kim… – Health informatics journal, 2020 – journals.sagepub.com
As “mukbang” (eating broadcast) becomes increasingly widespread, there is growing interest about the impact of mukbang on public health. This study aimed to analyze the content of mukbang YouTube v…

Analyzing bug fix for automatic bug cause classification
Z Ni, B Li, X Sun, T Chen, B Tang, X Shi – Journal of Systems and Software, 2020 – Elsevier
… code. Nguyen et al. (2013) introduced SLAMC, a novel statistical semantic language model for source code. It incorporates semantic information into code tokens and models the patterns of such semantic annotations. Their …

Polysemy and Synonymy Detection in Ontology Engineering
A CHALEPLIOGLOU, S PAPAVLASOPOULOS… – researchgate.net
… biomedical and health informatics, Vol.19, 2015, pp. 971-978. [8] FA Nielsen, LK Hansen, Creating semantic representations. In: S. Sikström, D. Garcia (eds.), Statistical Semantics, Springer, 2020. [9] C. Fellbaum, K. Brown, WordNet and wordnets. In: Brown, Keith et al …

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs
B Rozemberczki, O Kiss, R Sarkar – Proceedings of the 29th ACM …, 2020 – dl.acm.org
Page 1. Karate Club: An API Oriented Open-Source Python Framework for Unsupervised Learning on Graphs Benedek Rozemberczki The University of Edinburgh Edinburgh, United Kingdom benedek.rozemberczki@ed.ac.uk …

Graphical Causal Models and Imputing Missing Data: A Preliminary Study
RJ Almeida, G Adriaans, Y Shapovalova – International Conference on …, 2020 – Springer
… arXiv preprint arXiv:1309.6849. 16. Mooij, JM, Magliacane, S., Claassen, T.: Joint causal inference from multiple contexts. arXiv preprint arXiv:1611.10351 (2016). 17. Pearl, J., Verma, TS: A statistical semantics for causation. Stat. Comput. 2(2), 91–95 (1992) …

Comprehension Correlates of the Occurrence and Deletion of “de” in Mandarin “N1 (de) N2” Structures
J Zhao, J Wu – International Journal of Asian Language Processing, 2020 – World Scientific
… 20. J. Sun, ‘Jieba’ Chinese Word Segmentation Tool (2012). 21. R. Rehurek and P. Sojka, Gensim — statistical semantics in python, Statistical Seman- tics; Gensim; Python; LDA; SVD (2011). 22. F. Pedregosa et al., Scikit-learn: Machine Learning in Python, J. Mach. Learn …

Applying VSM to Identify the Criminal Meaning of Texts
NF Khairova, A Kolesnyk, O Mamyrbayev… – 2020 – repository.kpi.kharkov.ua
Page 1. Applying VSM to Identify the Criminal Meaning of Texts Nina Khairova1 [0000-0002-9826-0286], Anastasiia Kolesnyk1 [0000-0001-5817-0844], Orken Mamyrbayev2 [0000-0001-8318-3794] and Svitlana Petrasova1 [0000-0001-6011-135X] …

An Analysis of the Allergy Comments on Twitter Using Data Mining Approach
J Zhou – 2020 – cdr.lib.unc.edu
… Page 19. 17 Methods Our approach uses statistical, semantic and linguistics analysis for disclosing health characteristics of opinions in tweets talking about allergy. The present study includes data collection, data preprocessing, topic discovery, and topic-content analysis …

Neural Dialogue State Tracking with Temporally Expressive Networks
J Chen, R Zhang, Y Mao, J Xu – arXiv preprint arXiv:2009.07615, 2020 – arxiv.org
Page 1. arXiv:2009.07615v1 [cs.CL] 16 Sep 2020 Neural Dialogue State Tracking with Temporally Expressive Networks Junfan Chen BDBC and SKLSDE Beihang University, China chenjf@act.buaa.edu.cn Richong Zhang? BDBC …

A CONTEMPORARY SURVEY ON INTELLIGENT HUMAN-ROBOT INTERFACES FOCUSED ON NATURAL LANGUAGE PROCESSING
I Giachos, D Piromalis, M Papoutsidakis, S Kaminaris… – 2020 – researchgate.net
… workflow. A little more specific in the field of interest herein, a statistical semantic parser has been built that works: (i) on Speech and morpho-syntactic analysis (Speech re- ranking); (ii) on Semantic parsing; (iii) and Grounding …

Statistical Analysis of Dispelling Rumors on Sina Weibo
Y Wu, M Deng, X Wen, M Wang, X Xiong – Complexity, 2020 – hindawi.com
Journals; Publish with us; Publishing partnerships; About us; Blog. Complexity. +Journal Menu. PDF. Journal overview. For authorsFor reviewersFor editorsTable of Contents Special Issues.

Lexicon-Enhanced Transformer with Pointing for Domains Specific Generative Question Answering
J Yang, X Fu, S Wang, W Xie – … on Algorithms and Architectures for Parallel …, 2020 – Springer
… In: Advances in Neural Information Processing Systems, pp. 5998–6008 (2017)Google Scholar. 6. Furnas, GW, Landauer, TK, Gomez, LM, et al.: Human factors and behavioral science: statistical semantics: analysis of the potential performance of key-word information systems …

Implications of Implementation of Artificial Intelligence in the Banking Business in Relation to the Human Factor
K Ris, Ž Stankovi?… – JITA-JOURNAL OF …, 2020 – bibliotekabijeljina.rs.ba
… access: 11.12.2019. [2] Avramovi© Zoran ~, Dra?en Marinkovi©, Igor Lastri© (2017), Use of computer search algorithms in the research of statistical, semantic and contextual rules of language in digital information space. JITA ? …

Engines of order: A mechanology of algorithmic techniques
B Rieder – 2020 – library.oapen.org
Page 1. Amsterdam University Press BERNHARD RIEDER Engines of Order A Mechanology of Algorithmic Techniques Page 2. Engines of Order Page 3. The book series RECURSIONS: THEORIES OF MEDIA, MATERIALITY …

Semantic similarity and text summarization based novelty detection
S Kumar, KK Bhatia – SN Applied Sciences, 2020 – Springer
Current web crawlers search the queries at very high speed, but the problem of novelty detection or redundant information still persists. It consumes preci.

Informational Space of Meaning for Scientific Texts
N Suzen, EM Mirkes, AN Gorban – arXiv preprint arXiv:2004.13717, 2020 – arxiv.org
… determined by its use in scientific disciplines. This actu- ally matches the statistical semantics hypothesis that ‘statistical patterns of human word usage can be utilised to figure out what people mean’ [28]. We can also reword this as …

Recreational and philanthropic sectors are the worst-hit US industries in the COVID-19 aftermath
S Roy, R Dutta, P Ghosh – Social Sciences & Humanities Open – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Implicit Subspace Prior Learning for Dual-Blind Face Restoration
L Yang, P Wang, Z Gao, S Wang, P Ren, S Ma… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2020 1 Implicit Subspace Prior Learning for Dual-Blind Face Restoration Lingbo Yang, Pan Wang, Zhanning Gao, Peiran Ren, Shanshe Wang, Siwei Ma, Member, IEEE and Wen Gao, Fellow, IEEE …

An Empirical Exploration of Python Machine Learning API Usage
A Vilkomir – 2020 – thescholarship.ecu.edu
… outperform existing k-gram models, as well as RNN and LSTM deep-learning lan- guage models. Nguyen and Nguyen in [26] introduce the statistical semantic language model (SLAMC). This model proposes relying on the lexical analysis to capture the …

Implications of Implementation of Artificial Intelligence in the Banking Business with Correlation to the Human Factor
K Ris, Z Stankovic, Z Avramovic – Journal of Computer and …, 2020 – scirp.org
… in-banks; 8. Avramovic, Z., Marinkovic, D. and Lastric, I. (2017) Use of Computer Search Algorithms in the Research of Statistical, Semantic and Contextual Rules of Language in Digital Information Space. Journal of Information …

Twitter data in Emotional Analysis-A study
L Singh, P Gupta, R Katarya… – … on I-SMAC (IoT in Social …, 2020 – ieeexplore.ieee.org
Page 1. Twitter data in Emotional Analysis – A study Lokesh Singh Computer Engineering Delhi Technological University New Delhi, India. lokeshsingh.singh2@gmail.com Rahul Katarya Computer Science Department Delhi Technological University New Delhi, India …

Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces
A Freitas, S O’Riáin, E Curry – Real-time Linked Dataspaces, 2020 – Springer
… The principles of the Treo approach are generalised by constructing a distribu- tional semantic space (T-Space) for linked datasets [121]. The T-Space is built using a distributional semantic model based on statistical semantic information derived from Wikipedia …

Understanding the time course of privileged access to emotional knowledge in the brain: Evidence from ERPs and representational similarity analysis
V Sharpe – 2020 – search.proquest.com
Page 1. Understanding the time course of privileged access to emotional knowledge in the brain: Evidence from ERPs and representational similarity analysis A thesis submitted by Victoria Sharpe in partial fulfillment of the requirements for the degree of Master of Science in …

Intellicode compose: Code generation using transformer
A Svyatkovskiy, SK Deng, S Fu… – Proceedings of the 28th …, 2020 – dl.acm.org
Page 1. IntelliCode Compose: Code Generation using Transformer Alexey Svyatkovskiy? Microsoft Redmond, WA, USA alsvyatk@microsoft.com Shao Kun Deng? Microsoft Redmond, WA, USA shade@microsoft.com Shengyu …

Automating Mashup Service Recommendation via Semantic and Structural Features
W Xiong, Z Wu, B Li, B Hang – Mathematical Problems in Engineering, 2020 – hindawi.com
Journals; Publish with us; Publishing partnerships; About us; Blog. Mathematical Problems in Engineering. +Journal Menu. PDF. Journal overview. For authorsFor reviewersFor editorsTable of Contents Special Issues.

A Comparative Study of Vector Space Language Models for Sentiment Analysis Using Reddit Data
Y Liu – 2020 – search.proquest.com
… Sentiment Analysis Machine Learning Approach Lexicon based Approach Supervised Learning Unsupervised Learning Corpus based Approach VM Neural Network Naive Bayes Bayesian Network Statistical Semantic Sem s per se Lern ng Deep Lern ng …

Abbreviated three-item versions of the satisfaction with life scale and the harmony in life scale yield as strong psychometric properties as the original scales
ONE Kjell, E Diener – Journal of personality assessment, 2020 – Taylor & Francis
AbstractThe cognitive components of subjective well-being can be measured with the Satisfaction with life scale (SWLS) and the Harmony in life scale (HILS), which both comprise five items each. The…

e Space of Folklore: Mapping Folkloric Texts Semantically with Document Embeddings
B Rewis – 2020 – ling.yale.edu
… in a small dataset. 4.2 doc2vec for document embeddings We used Gensim’s library for scalable statistical semantics to run a PV-DM doc2vec model on the gathered folktales (Rehurek, 2010). While (Le, 2014) recommends …

Exploring the impact of COVID-19 on aviation industry: A text mining approach
S Gottipati, KJ Shim, AW Jiang… – 2020 11th IEEE Annual …, 2020 – ieeexplore.ieee.org
… Media Text. Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014. [19] Rehurek, R., Sojka, P. (2011) Gensim-statistical semantics in python. [20] McCallum, Andrew Kachites. “MALLET …

Time and Location Topic Model for analyzing Lihkg forum data
A Shen, KP Chow – 2020 13th International Conference on …, 2020 – ieeexplore.ieee.org
… “Linguistic regularities in continuous space word representations”. In Proceedings of NAACL-HLT, 2013, pages 746–751. [14] ?eh??ek R, Sojka P. “Gensim—statistical semantics in Python”. Retrieved from genism.org. 2011 …

Learning to code in a virtual world’ A Preliminary Comparative Analysis of Discourse and Learning in Two Online Programming Communities
S Sengupta – Conference Companion Publication of the 2020 on …, 2020 – dl.acm.org
… the Journal of machine Learning research 12 (2011), 2825–2830. [15] Radim ?eh?ek and Petr Sojka. 2011. Gensim—statistical semantics in python. Retrieved from genism. org (2011). [16] Samantha L Schneider and Martha Laurin Council. 2020 …

Spare me your medical mumbojumbo: A comparison among neural machine translation applications in the medical domain
L Gattini – 2020 – tesi.cab.unipd.it
… meanings taking into examination the immediate context of a word. He considered that statistical semantic could be very helpful in creating a machine able to translate from one language to another, with the contribution of cryptography. Of course, he was aware …

A survey of semantic relatedness evaluation datasets and procedures
MAH Taieb, T Zesch, MB Aouicha – Artificial Intelligence Review, 2020 – Springer
Semantic relatedness between words is a core concept in natural language processing. While countless approaches have been proposed, measuring which one wor.

Code prediction by feeding trees to transformers
S Kim, J Zhao, Y Tian, S Chandra – arXiv preprint arXiv:2003.13848, 2020 – arxiv.org
Page 1. Code Prediction by Feeding Trees to Transformers Seohyun Kim? Facebook Inc. USA skim131@fb.com Jinman Zhao? University of Wisconsin-Madison USA jz@cs.wisc.edu Yuchi Tian Columbia University USA yuchi.tian@columbia.edu Satish Chandra Facebook Inc …

Enhancing data quality in real-time threat intelligence systems using machine learning
A Rodriguez, K Okamura – Social Network Analysis and Mining, 2020 – Springer
In this research, we aim to expand the utility of keyword filtering on text-based data in the domain of cyber threat intelligence. Existing research-based.

P-NUT: Predicting NUTrient Content from Short Text Descriptions
G Ispirova, T Eftimov, B Korouši? Seljak – Mathematics, 2020 – mdpi.com
Assessing nutritional content is very relevant for patients suffering from various diseases, professional athletes, and for health reasons is becoming part of everyday life for many. However, it is a very challenging task as it requires complete and reliable sources. We introduce a machine …

Leveraging Cognitive Search Patterns to Enhance Automated Natural Language Retrieval Performance
B Selvaretnam, M Belkhatir – arXiv preprint arXiv:2004.10035, 2020 – arxiv.org
Page 1. Leveraging Cognitive Search Patterns to Enhance Automated Natural Language Retrieval Performance B. Selvaretnam Faculty of Computer Science Multimedia University selvaretnam@mmu.edu.my M. Belkhatir Faculty …

Evaluation of different text representation techniques and distance metrics using KNN for documents classification Evaluación de distintas técnicas de …
LA Calvo-Valverde, JA Mena-Arias – portal.amelica.org
… 2008, pp. 121–128. [11] S. Seifzadeh, AK Farahat, MS Kamel, F. Karray, Short-text clustering using statistical semantics, in: Proceedings of the 24th International Conference on World Wide Web, ACM, 2015, pp. 805–810. [12 …

Mining Hidden and Fragmented API Usages in Android Applications
M Kim, N Kim – Applied Sciences, 2020 – mdpi.com
Application Programming Interface (API) usage mining is an approach used to extract the common API usage to help developers get used to the APIs. However, in Android applications, the usage can be hidden or fragmented due to class inheritance. Such hidden or fragmented …

On-the-Fly Adaptation of Source Code Models using Meta-Learning
D Shrivastava, H Larochelle, D Tarlow – arXiv preprint arXiv:2003.11768, 2020 – arxiv.org
Page 1. On-the-Fly Adaptation of Source Code Models using Meta-Learning Disha Shrivastava 1 2 Hugo Larochelle 213 Daniel Tarlow 2 4 Abstract The ability to adapt to unseen, local contexts is an important challenge that successful models of source code must overcome …

Coalitions and coordination in Washington think tanks: board interlock among Washington DC-based policy research and planning organizations
AC Furnas – Applied Network Science, 2020 – Springer
Think tanks have become central players in the political and policy ecosystem of the United States, yet the communication and coordination strategies and connections between them remain relatively unexamined. This paper begins to remedy that by using IRS 990 data to construct …

Applying probabilistic models to C++ code on an industrial scale
A Shedko, I Palachev, A Kvochko, A Semenov… – Proceedings of the IEEE …, 2020 – dl.acm.org
Page 1. Applying probabilistic models to C++ code on an industrial scale Andrey Shedko?† a.shedko@samsung.com Samsung Research Russia Moscow, Russia Ilya Palachev? i.palachev@samsung.com Samsung Research Russia Moscow, Russia …

Deterministic Coresets for k-Means of Big Sparse Data
A Barger, D Feldman – Algorithms, 2020 – mdpi.com
Let P be a set of n points in R d , k ? 1 be an integer and ? ? ( 0 , 1 ) be a constant. An ?-coreset is a subset C ? P with appropriate non-negative weights (scalars), that approximates any given set Q ? R d of k centers. That is, the sum of squared distances over every point in P to …

Semantic Role Labeling as Syntactic Dependency Parsing
T Shi, I Malioutov, O ?rsoy – arXiv preprint arXiv:2010.11170, 2020 – arxiv.org
Page 1. Semantic Role Labeling as Syntactic Dependency Parsing Tianze Shi? Cornell University tianze@cs.cornell.edu Igor Malioutov Bloomberg LP imalioutov@bloomberg. net Ozan ?Irsoy Bloomberg LP oirsoy@bloomberg.net Abstract …

Impact of Combining Syntactic and Semantic Similarities on Patch Prioritization.
M Asad, KK Ganguly, K Sakib – ENASE, 2020 – researchgate.net
Page 1. Impact of Combining Syntactic and Semantic Similarities on Patch Prioritization Moumita Asad, Kishan Kumar Ganguly and Kazi Sakib Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh Keywords …

Emerging Topics in Brexit Debate on Twitter Around the Deadlines
E del Gobbo, S Fontanella, A Sarra… – Social Indicators …, 2020 – Springer
The present study is focused on the online debate relating to the Brexit process, three years and half since the historical referendum that has sanctioned.

API Misuse Detection Based on Stacked LSTM
S OuYang, F Ge, L Kuang, Y Yin – International Conference on …, 2020 – Springer
In modern software engineering, API (Application Programming Interface) is widely used to develop applications rapidly by reusing data structure, frameworks, class libs, and etc. However, due to the…

Semantic Unsupervised Automatic Keyphrases Extraction by Integrating Word Embedding with Clustering Methods
I Gagliardi, MT Artese – Multimodal Technologies and Interaction, 2020 – mdpi.com
Increasingly, the web produces massive volumes of texts, alone or associated with images, videos, photographs, together with some metadata, indispensable for their finding and retrieval. Keywords/keyphrases that characterize the semantic content of documents should be …

If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills
Z Xiao, MX Zhou, W Chen, H Yang, C Chi – Proceedings of the 2020 CHI …, 2020 – dl.acm.org
Page 1. If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills Ziang Xiao1*, Michelle X. Zhou2, Wenxi Chen3, Huahai Yang3, Changyan Chi3** 1zxiao5@illinois.edu, University of Illinois …

Learning Hierarchical Task Networks with Landmarks and Numeric Fluents by Combining Symbolic and Numeric Regression
M Fine-Morris, EDUB Auslander, MW Floyd, G Pennisi… – wbox0.cse.lehigh.edu
Page 1. Advances in Cognitive Systems X (20XX) 1-6 Submitted X/20XX; published X/20XX Learning Hierarchical Task Networks with Landmarks and Numeric Fluents by Combining Symbolic and Numeric Regression Morgan Fine-Morris1 MOF217@LEHIGH.EDU …

Névszói köt?hangzók variabilitásának korpuszalapú vizsgálata Corpus-based analysis of the variability of linking vowels in nouns and adjectives
R Péter, L Dániel – hlt.bme.hu
Page 1. EÖTVÖS LORÁND TUDOMÁNYEGYETEM Bölcsészettudományi Kar DIPLOMAMUNKA Névszói köt?hangzók variabilitásának korpuszalapú vizsgálata Corpus-based analysis of the variability of linking vowels in nouns and adjectives Témavezet?: Rebrus Péter, Ph.D …

SirenLess: reveal the intention behind news
X Chen, LYH Lo, H Qu – arXiv preprint arXiv:2001.02731, 2020 – arxiv.org
Page 1. Eurographics Conference on Visualization (EuroVis) 2020 M. Gleicher, T. Landesberger von Antburg, and I. Viola (Guest Editors) Volume 39 (2020), Number 3 SirenLess: reveal the intention behind news Xumeng Chen, Leo Yu-Ho Lo, Huamin Qu …

SCC++: predicting the programming language of questions and snippets of Stack Overflow
K Alrashedy, D Dharmaretnam, DM German… – Journal of Systems and …, 2020 – Elsevier
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Unsupervised dialectal neural machine translation
W Farhan, B Talafha, A Abuammar, R Jaikat… – Information Processing …, 2020 – Elsevier
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Evaluation of different text representation techniques and distance metrics using KNN for documents classification
LA Calvo-Valverde, JA Mena-Arias – Tecnología en marcha – portal.amelica.org
Nowadays, text data is a fundamental part in databases around the world and one of the biggest challenges has been the extraction of meaningful information …

Fast and Memory-Efficient Neural Code Completion
A Svyatkovskoy, S Lee, A Hadjitofi, M Riechert… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Fast and Memory-Efficient Neural Code Completion Alexey Svyatkovskiy alsvyatk@microsoft.com Microsoft Sebastian Lee ? sebalexlee@gmail.com University of Oxford, UK Anna Hadjitofi ? annahadjitofi@googlemail.com Alan Turing Institute, UK …

The Event Horizon Model and Long-Term Memory
JM Zacks – Ten Lectures on the Representation of Events in …, 2020 – brill.com
Jump to Content Jump to Main Navigation …

A network-based concept extraction for managing customer requests in a social media care context
M Misuraca, G Scepi, M Spano – International Journal of Information …, 2020 – Elsevier
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Sequence Model Design for Code Completion in the Modern IDE
GA Aye, GE Kaiser – arXiv preprint arXiv:2004.05249, 2020 – arxiv.org
Page 1. Sequence Model Design for Code Completion in the Modern IDE Gareth Ari Aye Google Inc., Columbia University aria@caa.columbia.edu Gail E. Kaiser Columbia University kaiser@cs.columbia.edu ABSTRACT Code …

InstaVis: Visualizing Clusters of Instagram Message Feeds
A Stöckl, J Diephuis, A Aschauer – researchgate.net
… “Visualization techniques for topic model checking.” In Twenty-Ninth AAAI Conference on Artificial Intelligence. 2015. [9] Rehurek, Radim, and Petr Sojka. “Gensim—statistical semantics in python.” Retrieved from genism. org (2011). 425 Page 5. Fig …

Survey on social networks data analysis
S Jaffali, S Jamoussi, N Khelifi… – … Conference on Innovations …, 2020 – Springer
Social networks are the most successful Web 2.0 applications, where users share and create over 2.5 quintillion bytes of data daily. This data can be exploited to retrieve many kinds of information…

Sentiment Analysis with ML Techniques: Handling Imbalanced Dataset
V RAJ – 2020 – dspace.dtu.ac.in
Page 1. Sentiment Analysis with ML Techniques: Handling Imbalanced Dataset A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF DEGREE OF MASTER OF TECHNOLOGY IN SOFTWARE ENGINEERING …

Hidden stories: Topic modeling in hydrology literature
M Rahman, J Frame, J Lin, G Nearing – 2020 – eartharxiv.org
Page 1. manuscript submitted to Water Resources Research Hidden Stories: Topic Modeling in Hydrology 1 Literature 2 Mashrekur Rahman1, Jonathan M. Frame1, Jimmy Lin2, Grey S. Nearing1,3 3 1Department of Geological …

Low-cost similarity calculation on ontology fusion in knowledge bases
W Lou, R Pi, H Wang, Y Ju – Journal of information science, 2020 – journals.sagepub.com
Ontology fusion in knowledge bases has become less easy, due to the massive capacity involved in the process of semantic similarity calculation. Many similarity calculation methods have been develo…

Graph embedding code prediction model integrating semantic features
K Yang, H Yu, G Fan, X Yang – Computer Science and Information …, 2020 – doiserbia.nb.rs
Page 1. Computer Science and Information Systems 00(0):0000–0000 https://doi.org/10.2298/ CSIS123456789X Graph Embedding Code Prediction Model Integrating Semantic Features Kang Yang1, Huiqun Yu1,2, Guisheng Fan1,3, and Xingguang Yang1 …

Teaching Natural Language Processing through Big Data Text Summarization with Problem-Based Learning
L Li, J Geissinger, WA Ingram… – Data and Information …, 2020 – content.sciendo.com
Jump to Content Jump to Main Navigation …

Validation of two short personality inventories using self-descriptions in natural language and quantitative semantics test theory
D Garcia, P Rosenberg, AA Nima, A Granjard… – Frontiers in …, 2020 – frontiersin.org
BackgroundIf individual differences are relevant and prominent features of personality, then they are expected to be encoded in natural language, thus manifesting themselves in single words. Recently, the quantification of text data using advanced natural language processing techniques …

Complexity Theory: Applications to Language Policy and Planning
M Civico – 2020 – archive-ouverte.unige.ch
Page 1. Thesis Reference Complexity Theory: Applications to Language Policy and Planning CIVICO, Marco Abstract Due to the fact that phenomena such as globalization, integration, migration, and progress in information …

A Preference-Based Approach for Representing Defaults in First-Order Logic
J Delgrande, C Rantsoudis – NMR 2020 Workshop Notes, 2020 – cs.sfu.ca
Page 1. A Preference-Based Approach for Representing Defaults in First-Order Logic James Delgrande, Christos Rantsoudis Simon Fraser University, Canada first last@sfu.ca Abstract A major area of knowledge representation …

A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning
F Liu, G Li, B Wei, X Xia, Z Fu, Z Jin – Proceedings of the 28th …, 2020 – dl.acm.org
Page 1. A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning Fang Liu1,2, Ge Li1,2†, Bolin Wei1,2, Xin Xia3, Zhiyi Fu1,2, Zhi Jin1,2† 1Key Laboratory of High Confidence Software Technologies …

Big code!= big vocabulary: Open-vocabulary models for source code
RM Karampatsis, H Babii, R Robbes… – 2020 IEEE/ACM …, 2020 – ieeexplore.ieee.org
Page 1. Big Code != Big Vocabulary: Open-Vocabulary Models for Source Code Rafael-Michael Karampatsis University of Edinburgh Edinburgh, United Kingdom Hlib Babii Free University of Bozen-Bolzano Bozen-Bolzano, Italy …

Survey of Automatic Spelling Correction
D Hládek, J Staš, M Pleva – Electronics, 2020 – mdpi.com
Automatic spelling correction has been receiving sustained research attention. Although each article contains a brief introduction to the topic, there is a lack of work that would summarize the theoretical framework and provide an overview of the approaches developed so far. Our …

Function completion in the time of massive data: A code embedding perspective
M Weyssow, H Sahraoui, B Vanderose… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Function completion in the time of massive data: A code embedding perspective Martin Weyssow DIRO, Université de Montréal Montreal, Canada Université de Namur Namur, Belgium martin.weyssow@umontreal.ca …

Modeling programs hierarchically with stack-augmented LSTM
F Liu, L Zhang, Z Jin – Journal of Systems and Software, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Crsal: Conversational recommender systems with adversarial learning
X Ren, H Yin, T Chen, H Wang, NQV Hung… – ACM Transactions on …, 2020 – dl.acm.org
Page 1. 34 CRSAL: Conversational Recommender Systems with Adversarial Learning XUHUI REN, HONGZHI YIN, and TONG CHEN, The University of Queensland, Australia HAO WANG, Alibaba Group, China NGUYEN QUOC …

Hidden Stories: Topic Modeling in Hydrologic
M Rahman, JM Frame, J Lin, GS Nearing – eartharxiv.org
Page 1. manuscript submitted to Water Resources Research Hidden Stories: Topic Modeling in Hydrologic 1 Literature 2 Mashrekur Rahman1, Jonathan M. Frame1, Jimmy Lin2, Grey S. Nearing1,3 3 1Department of Geological …

Does Creating an Artificial General Intelligence Require General Collective Intelligence in Order to Be Reliably Achievable?
AE Williams – 2020 – osf.io
Page 1. Does Creating an Artificial General Intelligence Require General Collective Intelligence in Order to be Reliably Achievable? Andy E. Williams, Nobeah Foundation, Nairobi, Kenya Abstract General Collective Intelligence …

Structuring Natural Language to Query Language: A Review
B Nethravathi, G Amitha, A Saruka, TP Bharath… – … , Technology & Applied …, 2020 – etasr.com
… [Online]. Available: http://arxiv.org/abs/1601.01280. [15] R. Ge and R. Mooney, “A Statistical Semantic Parser that Integrates Syntax and Semantics,” in Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005), Ann Arbor, Michigan, Jun …

Multi-task Learning based Pre-trained Language Model for Code Completion
F Liu, G Li, Y Zhao, Z Jin – 2020 35th IEEE/ACM International …, 2020 – ieeexplore.ieee.org
Page 1. Multi-task Learning based Pre-trained Language Model for Code Completion Fang Liu Key Lab of High Confidence Software Technology, MoE (Peking University) Beijing, China liufang816@pku.edu.cn Ge Li ? Key …

Introduction to Probabilistic Ontologies
R Peñaloza – Reasoning Web International Summer School, 2020 – Springer
There is no doubt about it; an accurate representation of a real knowledge domain must be able to capture uncertainty. As the best known formalism for handling uncertainty, probability theory is…

Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer
S Lee, HS Han, SK Cha, S Son – 29th {USENIX} Security Symposium …, 2020 – usenix.org
Page 1. ARTIFACT EVALUATED PASSED Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer Suyoung Lee, HyungSeok Han, Sang Kil Cha, Sooel Son School of Computing, KAIST Abstract JavaScript …

Logram: Efficient log parsing using n-gram dictionaries
H Dai, H Li, CS Chen, W Shang… – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
Page 1. 1 Logram: Efficient Log Parsing Using n-Gram Dictionaries Hetong Dai, Student Member, IEEE, Heng Li, Member, IEEE, Che-Shao Chen, Student Member, IEEE, Weiyi Shang, Member, IEEE, Tse-Hsun (Peter) Chen, Member, IEEE …

Combining distributed word representation and document distance for short text document clustering
S Kongwudhikunakorn… – Journal of Information …, 2020 – koreascience.or.kr
Page 1. www.kips.or.kr Copyright© 2020 KIPS Combining Distributed Word Representation and Document Distance for Short Text Document Clustering Supavit Kongwudhikunakorn* and Kitsana Waiyamai* Abstract This paper …

Deep code comment generation with hybrid lexical and syntactical information
X Hu, G Li, X Xia, D Lo, Z Jin – Empirical Software Engineering, 2020 – Springer
During software maintenance, developers spend a lot of time understanding the source code. Existing studies show that code comments help developers compreh.

The Pile: An 800GB Dataset of Diverse Text for Language Modeling
L Gao, S Biderman, S Black, L Golding… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe Charles Foster Jason Phang Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy EleutherAI contact@eleuther.ai …

Traces of Meaning Itself: Encoding distributional word vectors in brain activity
J Sassenhagen, CJ Fiebach – Neurobiology of Language, 2020 – MIT Press
Create a new account. Email. Returning user. Can’t sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …

An implicit aspect modelling framework for diversity focused query expansion
RE Dev, V Balasubramanian – Journal of Intelligent Information Systems, 2020 – Springer
Diversified Query Expansion aims to present the user with a diverse list of query expansions so as to better communicate their intent to the retrieval syst.

BRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives
RG Rodrigues, KT Rodrigues… – IEEE Latin America …, 2020 – ieeexplore.ieee.org
… 161–164. [13] K. Wo?k, W. Glinkowski, and A. ?Zukowska, “Enhancing the Assessment of (Polish) Translation in PROMIS Using Statistical, Semantic, and Neu- ral Network Metrics,” Advances in Intelligent Systems and Computing, vol. 746, pp. 351–366, 2018 …

Data Science in Chemistry: Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter
T Gressling – 2020 – books.google.com
Page 1. Thorsten Gressling Data Science in Chemistry Page 2. De Gruyter Textbook Page 3. De Gruyter Textbook Page 4. Thorsten Gressling Data Science in Chemistry Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter Page 5 …

Holistic Combination of Structural and Textual Code Information for Context based API Recommendation
C Chen, X Peng, Z Xing, J Sun, X Wang, Y Zhao… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. 1 Holistic Combination of Structural and Textual Code Information for Context based API Recommendation Chi Chen, Xin Peng, Member, IEEE, Zhenchang Xing, Jun Sun, Xin Wang, Yifan Zhao, and Wenyun Zhao Abstract …

Towards Semantic Role Labelling of Hindi-English Code-Mixed Data
R Pal – 2020 – web2py.iiit.ac.in
Page 1. Towards Semantic Role Labelling of Hindi-English Code-Mixed Data Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computational Linguistics by Research by Riya Pal 201425095 riya.pal@research.iiit.ac.in …

Site-Specific Rules Extraction in Precision Agriculture
FJ Zarazaga Soria, FJ López Pellicer – core.ac.uk
Page 1. 2020 19 Borja Antonio Espejo García Site-Specific Rules Extraction in Precision Agriculture Departamento Director/es Informática e Ingeniería de Sistemas Zarazaga Soria, Francisco Javier López Pellicer, Francisco Javier Page 2 …

Bridging the theoretical gap between semantic representation models without the pressure of a ranking: some lessons learnt from LSA
G Jorge-Botana, R Olmos, JM Luzón – Cognitive processing, 2020 – Springer
In recent years, latent semantic analysis (LSA) has reached a level of maturity at which its presence is ubiquitous in technology as well as in simulation.

Improving Code Completion in Pharo Using N-gram Language Models
M ROMANIUK – 2020 – researchgate.net
Page 1 …

Improving the Robustness to Data Inconsistency between Training and Testing for Code Completion by Hierarchical Language Model
Y Yang – arXiv preprint arXiv:2003.08080, 2020 – arxiv.org
… [Online]. Available: http://dx.doi.org/10.1109/ICSE.2012.6227135 [9] TT Nguyen, AT Nguyen, HA Nguyen, and TN Nguyen, “A statistical semantic language model for source code,” in ESEC/FSE’13, Saint Petersburg, Russian Federation, August 18-26, 2013, 2013, pp. 532–542 …

Models of lexical meaning
P Acquaviva, A Lenci, C Paradis… – Word Knowledge and …, 2020 – library.oapen.org
Page 361. Paolo Acquaviva, Alessandro Lenci, Carita Paradis and Ida Raffaelli Models of lexical meaning Abstract: Lexical semantics is concerned with modeling the meaning of lexical items. Its leading questions are how forms …

Omnichannel path to purchase: Viability of Bayesian Network as Market Attribution Models
A Dikshit – 2020 – diva-portal.org
Page 1. Linköpings universitet SE– Linköping + , www.liu.se Linköping University | Department of Computer and Information Science Master’s thesis, 30 ECTS | Statistics and Machine Learning 2020 | LIU-IDA/STAT-A–20/003–SE Omnichannel path to purchase …

Building Ethical AI from News Articles
W Kim, K Lee – 2020 IEEE/ITU International Conference on …, 2020 – ieeexplore.ieee.org
Page 1. XXX-X-XXXX-XXXX-X/XX/$XX.00 ©20XX IEEE Building Ethical AI from News Articles Wonchul Kim Graduate school of Communication Yonsei University South Korea wkim8905@yonsei.ac.kr Keeheon Lee Underwood …

logram: efficient log paring using n-gram model
H Dai – 2020 – spectrum.library.concordia.ca
Page 1. LOGRAM: EFFICIENT LOG PARSING USING N-GRAM DICTIONARIES Hetong Dai A thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements For the Degree of Master of Computer Science …

Augmenting Machine Learning with Information Retrieval to Recommend Real Cloned Code Methods for Code Completion
M Hammad, Ö Babur, HA Basit – arXiv preprint arXiv:2010.00964, 2020 – arxiv.org
Page 1. Augmenting Machine Learning with Information Retrieval to Recommend Real Cloned Code Methods for Code Completion Muhammad Hammad Eindhoven University of Technology Netherlands m.hammad@tue.nl …

Learning Autocompletion from Real-World Datasets
GA Aye, S Kim, H Li – arXiv preprint arXiv:2011.04542, 2020 – arxiv.org
Page 1. Learning Autocompletion from Real-World Datasets Gareth Ari Aye Facebook Inc. Menlo Park, USA gaa@fb.com Seohyun Kim Facebook Inc. Menlo Park, USA skim131@fb.com Hongyu Li Facebook Inc. Menlo Park, USA hongyul@fb.com …

Why do items correlate with one another? A conceptual analysis with relevance for general factors and network models
D Leising, J Burger, J Zimmermann, M Bäckström… – 2020 – psyarxiv.com
Page 1. General factors in person judgment data 1 This paper is currently under review Why do items correlate with one another? A conceptual analysis with relevance for general factors and network models Daniel Leising12 …

Heuristic and Neural Network based Prediction of Project-Specific API Member Access
L Jiang, H Liu, H Jiang, L Zhang… – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
Page 1. 0098-5589 (c) 2020 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …

Confronting Sparseness and High Dimensionality in Short Text Clustering via Feature Vector Projections
L Akritidis, M Alamaniotis, A Fevgas… – 2020 IEEE 32nd …, 2020 – ieeexplore.ieee.org
Page 1. Confronting Sparseness and High Dimensionality in Short Text Clustering via Feature Vector Projections Leonidas Akritidis School of Science and Technology Int’l Hellenic University Thessaloniki, Greece Email: lakritidis@ihu.gr …

Querying subjective data
Y Li, A Feng, J Li, S Chen, S Mumick, A Halevy, V Li… – The VLDB Journal, 2020 – Springer
Online users are constantly seeking experiences, such as a hotel with clean rooms and a lively bar, or a restaurant for a romantic rendezvous. However, ec.

CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis
G Zhang, MA Merrill, Y Liu, J Heer, T Althoff – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis Ge Zhang?§, Mike A. Merrill†§, Yang Liu†, Jeffrey Heer†, Tim Althoff† ? Department of Computer Science …

Fret: Functional Reinforced Transformer With BERT for Code Summarization
R Wang, H Zhang, G Lu, L Lyu, C Lyu – IEEE Access, 2020 – ieeexplore.ieee.org
Page 1. Received May 30, 2020, accepted July 21, 2020, date of publication July 24, 2020, date of current version August 4, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3011744 Fret: Functional Reinforced Transformer With BERT for Code Summarization …

Topic modeling in short-text using non-negative matrix factorization based on deep reinforcement learning
Z Shahbazi, F Jamil, Y Byun – Journal of Intelligent & Fuzzy …, 2020 – content.iospress.com
Page 1. Journal of Intelligent & Fuzzy Systems 39 (2020) 753–770 DOI:10.3233/ JIFS-191690 IOS Press 753 Topic modeling in short-text using non-negative matrix factorization based on deep reinforcement learning Zeinab …

Towards Automated Security Validation for Hardware Designs
R Zhang – 2020 – cdr.lib.unc.edu
Page 1. TOWARDS AUTOMATED SECURITY VALIDATION FOR HARDWARE DESIGNS Rui Zhang A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements …

THESIS/THÈSE
M WEYSSOW – researchportal.unamur.be
Page 1. Institutional Repository – Research Portal Dépôt Institutionnel – Portail de la Recherche THESIS / THÈSE Author(s) – Auteur(s) : Supervisor – Co-Supervisor / Promoteur – Co-Promoteur : Publication date – Date de publication : Permanent link – Permalien …

Competition analysis on the over-the-counter credit default swap market
L Abraham – arXiv preprint arXiv:2012.01883, 2020 – arxiv.org
Page 1. Competition analysis on the over-the-counter credit default swap market Louis Abraham July 2020 arXiv:2012.01883v1 [cs.LG] 3 Dec 2020 Page 2. Page 3. Abstract We study two questions related to competition on the …

Natural Language Visual Grounding via Multimodal Learning
J Mi – 2020 – ediss.sub.uni-hamburg.de
Page 1. Natural Language Visual Grounding via Multimodal Learning Dissertation with the aim of achieving the degree of Doctor rerum naturalium (Dr. rer. nat.) at the Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Universität Hamburg …

Bibliometric visualization and analysis software: State of the art, workflows, and best practices
ME Bales, DN Wright, PR Oxley, TR Wheeler – 2020 – ecommons.cornell.edu
Page 1. Bibliometric Visualization and Analysis Software: State of the Art, Workflows, and Best Practices Michael E. Bales, Drew N. Wright, Peter R. Oxley*, and Terrie R. Wheeler*1 *These authors contributed equally to the work …

Caught-in-Translation (CiT): Detecting Cross-level Inconsistency Attacks in Network Functions Virtualization
S Lakshmanan Thirunavukkarasu – 2020 – spectrum.library.concordia.ca
Page 1. Caught-in-Translation (CiT): Detecting Cross-level Inconsistency Attacks in Network Functions Virtualization Sudershan Lakshmanan Thirunavukkarasu A Thesis in The Department of Concordia Institute for Information Systems Engineering …

Deep Learning for Source Code Modeling and Generation: Models, Applications, and Challenges
THM Le, H Chen, MA Babar – ACM Computing Surveys (CSUR), 2020 – dl.acm.org
Page 1. 62 Deep Learning for Source Code Modeling and Generation: Models, Applications, and Challenges TRIET HM LE, HAO CHEN, and MUHAMMAD ALI BABAR, The University of Adelaide Deep Learning (DL) techniques …