Automatic Machine Learning & Natural Language 2017


Notes:

  • Automated machine learning
  • AutoML

Resources:

  • auto-sklearn .. automated machine learning toolkit (drop-in replacement for a scikit-learn estimator)
  • autograd .. efficiently computes derivatives of numpy code
  • autokit .. automatic machine learning suite
  • autoweka .. selects a learning algorithm and sets its hyperparameters
  • hyperopt .. distributed asynchronous hyperparameter optimization in python

Wikipedia:

References:

See also:

100 Best Google AutoML Videos | Machine Learning Meta Guide


Automatic differentiation variational inference
A Kucukelbir, D Tran, R Ranganath, A Gelman… – The Journal of Machine …, 2017 – jmlr.org
… It has had an impact on myriad applications in both statistics and machine learning, including natural language processing, speech recognition, computer vision, population genetics, and computational neuroscience. Figure 14 presents an example …

A machine learning approach for classifying textual data in crowdsourcing
M Rhyn, I Blohm – 2017 – aisel.aisnet.org
… Finally, our automated machine learning and text mining approach also contributes to practitioners in the domain of software testing … In: Proceedings of the 2007 Join Conference on Empirical Methods in Natural Language Processing and Computational Natural Language …

A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
A Holzinger, M Plass, K Holzinger, GC Crisan… – arXiv preprint arXiv …, 2017 – arxiv.org
… Consequently, automatic machine learning (aML) works well when having large amounts of training data (Sonnenburg et al., 2006 … How- ever, aML-algorithms have enormous problems when lacking contextual information, eg in natural language translation/curation, or in …

General Symptom Extraction from VA Electronic Medical Notes.
G Divita, G Luo, LT Tran, TE Workman… – Studies in health …, 2017 – europepmc.org
… The text from clinical records are an additional source of signs and symptoms. We describe a Natural Language Processing (NLP) technique to identify symptoms from text … The technique includes a model created from an automatic machine learning model selection tool …

Machine learning vortices at the Kosterlitz-Thouless transition
MJS Beach, A Golubeva, RG Melko – arXiv preprint arXiv:1710.09842, 2017 – arxiv.org
… I. INTRODUCTION The remarkable success of artificial neural networks in the tasks of image recognition and natural language pro- cessing has prompted interdisciplinary efforts to investi- gate how these new tools might benefit a broad range of sciences …

A system for accessible artificial intelligence
RS Olson, M Sipper, W La Cava, S Tartarone… – arXiv preprint arXiv …, 2017 – arxiv.org
… can aid in this endeavor, and highlight specific examples where genetic programming has automated machine learning analyses in … 5]. The Watson AI system that won Jeopardy combined knowledge representation, information retrieval, natural language processing, and …

An analysis of machine-and human-analytics in classification
GKL Tam, V Kothari, M Chen – IEEE transactions on …, 2017 – ieeexplore.ieee.org
… (i) We used automated machine-learning processes to constructed a decision tree based on a collection of fea … This is referred to as the bag of features method [16], which is derived from the bag of words method in natural language processing and information retrieval [24] …

One button machine for automating feature engineering in relational databases
HT Lam, JM Thiebaut, M Sinn, B Chen, T Mai… – arXiv preprint arXiv …, 2017 – arxiv.org
… configuration and preprocessing work-flow. Automatic Statistician [9] is similar to the works just described but focuses more on time-series data and interpretation of the models in natural language. In summary, automation of hyper …

Machine Learning for Identifying Emotional Expression in Text: Improving the Accuracy of Established Methods
EOC Bantum, N Elhadad, JE Owen, S Zhang… – Journal of Technology in …, 2017 – Springer
… The goal of the current study was to create an automated machine learning technique to mimic manual coding … Named Entity Recognition (using Stanford NER) (The Stanford Natural Language Processing Group, 2006) was performed so that Person, Location, and Organization …

Accuracy of an automated knowledge base for identifying drug adverse reactions
EA Voss, RD Boyce, PB Ryan, J van der Lei… – Journal of biomedical …, 2017 – Elsevier
… in a method described by Avillach et al. [23] and the second used relationships semantically tagged Medline abstracts via natural language processing from SemMedDB [24]. These two methods are additionally stratified by …

Classification of Journal Articles in a Search for New Experimental Thermophysical Property Data: a Case Study
A Peskin, A Dima – Integrating Materials and Manufacturing Innovation, 2017 – Springer
… At the fifth step, we had the option to use automated machine learning techniques, but we instead chose to examine the nuances of this data … Topic modeling refers to a set of techniques for finding abstract topics in a natural language corpus [5]. A document can be represented …

Machine learning models for multidimensional clinical data
C Orphanidou, D Wong – Handbook of Large-Scale Distributed Computing …, 2017 – Springer
Healthcare monitoring systems in the hospital and at home generate large quantities of rich-phenotype data from a wide array of sources. Typical sources include clinical observations, continuous wavef.

Social human-robot interaction for the elderly: two real-life use cases
A Zlatintsi, I Rodomagoulakis, V Pitsikalis… – Proceedings of the …, 2017 – dl.acm.org
… of cases eg, social companions [1], to ones that deal with dementia [8] and disorders [3]; (3) as a consequence of the core machine learning advancements, with deep learning in natural language processing, computer … specific datasets and automatic machine learning tools …

Evaluation of entity recognition algorithms in short texts
RF Canales, EC Murillo – CLEI ELECTRONIC JOURNAL, 2017 – clei.org
… Named Entity Recognition has a pivotal role in two well-known Natural Language Processing (NLP) tasks: sentiment analysis and … Automatic machine learning is an alternative to handcrafted rules for automatically induce rule-based sys- tems or sequence labeling algorithms …

A machine learning approach to product review disambiguation based on function, form and behavior classification
A Singh, CS Tucker – Decision Support Systems, 2017 – Elsevier
Skip to main content …

Toward Multimodal Cyberbullying Detection
VK Singh, S Ghosh, C Jose – Proceedings of the 2017 CHI Conference …, 2017 – dl.acm.org
… Just as in the early days of natural language processing, the accuracy of these individual detectors varies greatly (typically ranging … Classification In this work, we attempt to build an automatic machine learning based classifier to detect media sessions con- taining cyberbullying …

Using Machine Learning to Improve Internet Privacy
S Zimmeck – 2017 – sebastianzimmeck.de
… Further, I demonstrate how the current notice-and-choice paradigm can be realized by automated machine learning privacy policy analysis. The implemented sys … to use what is already there—privacy policies in natural language. As of now, Massey et al. [189] …

Copycats versus original mobile apps: A machine learning copycat detection method and empirical analysis
Q Wang, B Li, P Singh – 2017 – papers.ssrn.com
… original. Using a combination of machine learning techniques such as natural language processing, latent … 4.1 Step 1: Detecting Functional Similarity Based on Textual Descriptions and Customer Reviews Using Natural Language Procession (NLP) …

Sharing Annotated Audio Recordings of Clinic Visits With Patients—Development of the Open Recording Automated Logging System (ORALS): Study …
PJ Barr, MD Dannenberg, CH Ganoe… – JMIR research …, 2017 – ncbi.nlm.nih.gov
… ORALS will consist of 2 key elements: (1) technically proficient software using automated machine learning technology to enable accurate and automatic … We will implement the automated tagging software using the Weka, Natural Language Toolkit, and SciKit libraries in Python …

DeepFlow: deep learning-based malware detection by mining Android application for abnormal usage of sensitive data
D Zhu, H Jin, Y Yang, D Wu… – … (ISCC), 2017 IEEE …, 2017 – ieeexplore.ieee.org
… a lot of attentions in the field of artificial intelligence and has numerous applications in image classification, natural language processing, etc … SUSI is an automated machine learning guided approach for identifying sources and sinks directly from the code of an Android API …

Estimating the number of remaining links in traceability recovery
D Falessi, M Di Penta, G Canfora… – Empirical Software …, 2017 – Springer
… terms include: 1) Simple extraction (tokenization and stop-word removal) and 2) Part Of Speech (POS) Tagging using the Stanford natural language parser, which … On top of Weka we developed a tool called ATHLETE (Automated macHine LEarning Techniques Evaluation) …

Survey on clinical prediction models for diabetes prediction
N Jayanthi, BV Babu, NS Rao – Journal of Big Data, 2017 – Springer
… To do this it makes use of statistical analysis techniques, analytical queries and automated machine learning algorithms … 12], logistic regression [11, 12, 14], neural networks (NNs) [11, 12, 13], machine learning, support vector machines (SVMs), natural language processing (NLP …

Natural Language Video Processing (Machine Learning-based Identification, Search, Extraction)
N Frey, L Thompson, J Chien, W Norris, B Mulford – 2017 – tdcommons.org
… Defensive Publications Series October 14, 2017 Natural Language Video Processing (Machine Learning-based Identification, Search, Extraction) Nathan Frey … Page 2. -1- Natural Language Video Processing (Machine Learning-based Identification, Search, Extraction) …

A computational model for automatic generation of domain-specific dialogues using machine learning
A Vázquez, D Pinto, D Vilariño – … of the XVIII International Conference on …, 2017 – dl.acm.org
… Computing methodologies ? Machine Learning ? Learning paradigms ? Supervised learning; • Artificial intelligence ? Natural language processing … The second contribution will be a proposed computational model based on automatic machine learning techniques that will …

Automatic Arabic Summarization: A survey of methodologies and systems
LM Al Qassem, D Wang, Z Al Mahmoud… – Procedia Computer …, 2017 – Elsevier
… Keywords: Automatic Text Summarization; Arabic Summarization systems; Arabic Natural Language Processing * Corresponding author … Numerical Boudabous et al. 2010 [24] Authors’ corpus Automatic Machine Learning Generic Single-document …

Framework of sentiment annotation for document specification in Indonesian language base on topic modeling and machine learning
T Sutabri, M Ardiansyah – Cyber and IT Service Management …, 2017 – ieeexplore.ieee.org
… In machine learning and natural language processing, the topic model is a statistical model to find the kind of abstract “topics” that occur in the document … Distant supervision techniques to reduce human supervision in the process of annotation (automatic machine learning) …

Towards Integrative Machine Learning and Knowledge Extraction
A Holzinger, R Goebel, V Palade, M Ferri – Towards Integrative Machine …, 2017 – Springer
… He emphasized that automatic machine learning algorithms aiming at bringing the human-out-of-the-loop [13] have demonstrated impressive … Sou-Cheng and her colleagues adapt natural language processing (NLP) techniques and data-mining methods to train powerful …

Predicting Budget from Transportation Research Grant Description: An Exploratory Analysis of Text Mining and Machine Learning Techniques
A Singhal, K Gopalakrishnan… – Soft Computing in Civil …, 2017 – jsoftcivil.com
… Natural Language Processing (NLP) based text representation models such as the Latent Dirichlet Allocation (LDA), Latent Semantic Indexing (LSI … We proposed a fully automated machine learning approach to predict the approximate budget for a research project, given a short …

Machine Learning and Social Media in Crisis Management: Agility vs Ethics
V Lanfranchi – … of the 14th International Conference on …, 2017 – eprints.whiterose.ac.uk
… to exploit social media and crowdsourcing during emergency, many of them adopting automatic or semi-automatic Machine Learning (ML) algorithms … extent, researchers have worked to create algorithms that analyse the information using NLP (Natural Language Processing) or …

5-Page Personal Research Statement: Machine Learning & Knowledge Extraction (MAKE)
A Holzinger – aholzinger.at
… However, the application of automatic machine learning (aML) algorithms in complex domains (eg Health) seems elusive at present … The best practice examples today are autonomous vehicles, recommender systems, or natural language understanding [2], [3]. To see health …

An automatic gender detection from non-normative Lithuanian texts
M Briedien?, J Kapo?i?t?-Dzikien? – 2017 – pdfs.semanticscholar.org
… Abstract—This paper describes the gender detection research done on Lithuanian texts using automatic machine learning methods … I. INTRODUCTION Due to the constant increase of electronic texts the various natural language processing works become especially relevant …

Review on Computing Machinery and Intelligence
SK Jyoti, KD Manjusha, KD Pavan – ijcmas.com
… Machine learning control Machine perception Medical diagnosis Economics Insurance Natural language processing Natural language understanding Optimization … of medical doctors jobs would be lost in the next two decades to automated machine learning medical diagnostic …

A semantic framework for sequential decision making for journal of web engineering
P Philipp, M Maleshkova, A Rettinger… – Journal of Web …, 2017 – dl.acm.org
… Klein , Katharina Eggensperger , Jost Tobias Springenberg , Manuel Blum , Frank Hutter, Efficient and robust automated machine learning, Proceedings of the … of named entities in text, Proceedings of the Conference on Empirical Methods in Natural Language Processing, July …

Materializing the Promises of Cognitive IoT: How Cognitive Buildings are Shaping the Way
J Ploennigs, A Ba, M Barry – IEEE Internet of Things Journal, 2017 – ieeexplore.ieee.org
… The integration of speech interfaces such as Amazon Echo shows great potential to interact in natural language with the operators and occupants. Also augmented reality interfaces are paving new ways to seamlessly access to sensors and systems data …

Image Recognition with Histogram of Oriented Gradient Feature and Pseudoinverse Learning AutoEncoders
S Feng, S Li, P Guo, Q Yin – International Conference on Neural …, 2017 – Springer
… Neural network is an artificial intelligence technology which achieve good results in computer vision, natural language processing and other related fields … This is our effort to prompt the development of automatic machine learning and expect to democratize artificial intelligence …

Group-In-The-Loop: Architecture For Harnessing And Creating Collective Intelligence
SN Haider, SC Haw, FF Chua – icoci.cms.net.my
… machine learning approaches greatly benefit from the presence of big data, in rule based environments. However, there can be situations when automatic approaches may deliver unsatisfactory result in the absence of adequate contextual informaiton, eg, in natural language …

Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach
H Müller, R Reihs, K Zatloukal – … , Banff, AB, Canada, July 24-26 …, 2017 – books.google.com
… multi-agent-hybrid systems. 2 Glossary and Key Terms Automatic Machine Learning (aML) in bringing the human-out-of-the-loop is the grand goal of ML and works well in many cases having “big data”[11]. Big Data is indicating …

The Practical Concepts of Machine Learning
P Kashyap – Machine Learning for Decision Makers, 2017 – Springer
… manipulation. Deep Learning: Techniques and algorithms are being used to identify specific objects in images and carry out natural language processing … type. Automated Machine Learning Based Customer Support Systems …

BoostClean: Automated Error Detection and Repair for Machine Learning
S Krishnan, MJ Franklin, K Goldberg, E Wu – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. BoostClean: Automated Error Detection and Repair for Machine Learning Sanjay Krishnan?, Michael J. Franklin?†, Ken Goldberg?, Eugene Wu†† ?UC Berkeley, †University of Chicago, ††Columbia University {sanjaykrishnan …

Adaptive contents for interactive TV guided by machine learning based on predictive sentiment analysis of data
VM Mondragon, V García-Díaz, C Porcel, RG Crespo – Soft Computing, 2017 – Springer
… and defines terms related to the analysis of sentiment and com- pares the techniques in the implementation of the Automatic machine learning … of the ontology domain, making a semantic analysis of the obtained tweets using the process- ing of natural language to classify the …

Interactive Data Analytics for the Humanities
I Gurevych, CM Meyer, C Binnig, J Fürnkranz… – download.visinf.tu-darmstadt.de
… Our vision links natural language processing research with recent advances in machine learning, computer vision, and data management systems, as realizing this vision relies on combining expertise from all of these scientific fields. 1 Challenges in Analyzing Humanities Data …

FeatureHub: Towards collaborative data science
MJ Smith, R Wedge, K Veeramachaneni – micahsmith.com
… Our platform includes an automated machine learning backend which abstracts model training, selection, and tuning, allowing users to focus on feature engineering while still receiving … In this step, they are also asked to provide a description of the feature in natural language …

A Two-Stage Machine learning approach for temporally-robust text classification
T Salles, L Rocha, F Mourão, M Gonçalves, F Viegas… – Information Systems, 2017 – Elsevier
… most cases, with large reductions in execution time. Keywords. Automatic document classification. Temporal weighting function. Fully-Automated machine learning process. 1. Introduction. Text classification is still one of the major …

Big Data Analytics and Visualization: Finance
S Prabhakar, L Maves – Big Data and Visual Analytics, 2017 – Springer
… Big Data computing infrastructures are making it practical to employ automated machine learning algorithms for this purpose (Fig. 1). Open image in new window. Fig. 1 … 4 Big Data for Sentiment Analysis Using Natural Language Programming …

Integrated Machine-Learning Algorithm for Identifying Segment-Level Key Drivers from Consumers’ Online Review Data
S Kim – 2017 – aisel.aisnet.org
… As such, large amounts of various online review data (eg, numerical star ratings, textual reviews in natural language) are publicly available, and these reviews include the direct but heterogeneous opinions of consumers about products or services …

Classifying and Mining Job Ads Pertaining to the Offshore Sector in Casablancaa
M ELOUALI – ghitamezzour.com
… This is why I chose to develop an automated machine learning classification system to classify offshore ads … 2.1 Bag of words The bag-of-words model is a simplified representation used in natural language processing and information retrieval (IR) …

Privacy as Protection of the Incomputable Self: Agonistic Machine Learning
M Hildebrandt – 2017 – papers.ssrn.com
… Though this also goes for natural language, human language can also do what it describes,29 thus presenting rather than representing a shared world: ‘I declare you man and wife’ is not a description but an act that institutes what it describes …

Automatically Tracking Metadata and Provenance of Machine Learning Experiments
S Schelter, JH Böse, J Kirschnick, T Klein, S Seufert – pdfs.semanticscholar.org
… Natural Language Engineering, 10(3-4):327–348, 2004. [10] Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum, and Frank Hutter. Efficient and robust automated machine learning. In NIPS, pages 2962–2970, 2015 …

Spam Detection on Social Media Text
G Jain, B Manisha – 2017 – ijcseonline.org
… However, the success of these methods is limited and they need to be combined with automatic machine learning methods in order to … III. EXERIMENTAL SETUP A. Preprocessing The natural language used in social media text is not structured and does not follow the language …

Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach
A Holzinger, B Malle, P Kieseberg, PM Roth… – … Machine Learning and …, 2017 – Springer
… multi-agent-hybrid systems. 2 Glossary and Key Terms. Automatic Machine Learning (aML) in bringing the human-out-of-the-loop is the grand goal of ML and works well in many cases having “big data” [11]. Big Data is indicating …

Automatic approval prediction for software enhancement requests
ZA Nizamani, H Liu, DM Chen, Z Niu – Automated Software Engineering, 2017 – Springer
… Wang et al. (2008) applied natural language processing techniques to suggest a list of most similar existing reports to the new report … 2009). Anvik et al. (2006) proposed a semi-automated machine learning based algorithm for the assignment of reports to relevant developers …

Constrained Bayesian Optimization for Automatic Chemical Design
RR Griffiths – arXiv preprint arXiv:1709.05501, 2017 – arxiv.org
Page 1. Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths Department of Engineering University of Cambridge This dissertation is submitted for the degree of Master of Philosophy Wolfson College August 2017 …

StanceXplore: Visualization for the Interactive Exploration of Stance in Social Media
RM Martins, V Simaki, K Kucher, C Paradis… – 2nd Workshop on …, 2017 – blogg.lnu.se
… doi: 10. 1111/cgf.13181 [10] KS Hasan and V. Ng. Why are you taking this stance? Identifying and classifying reasons in ideological debates. In Proceedings of the 2012 Conference on Empirical Methods on Natural Language Processing, vol. 14 of EMNLP 2014, pp. 751–762 …

Deep Learning with Deep Water
WPMSM Dymczyk, ACQ Kou – 2017 – docs.h2o.ai
… and recurrent neural networks, along with novel building blocks like Inception modules and residual networks, continue to demonstrate ground breaking results in many areas of artificial intelligence, including computer vision, speech, audio, and natural language processing …

Machine Learning in Automating Supply Management Maturity Ratings
YY Huang – 2017 – search.proquest.com
… Automated TC involves several important disciplines such as Information Retrieval. (IR), Natural Language Processing (NLP), and Artificial Intelligence (AI). Early studies on … This approach is called Bag-of-words (BoW),. which was derived from natural language processing …

Automatically Classifying User Requests in Crowdsourcing Requirements Engineering
C Li, L Huang, J Ge, B Luo, V Ng – Journal of Systems and Software, 2017 – Elsevier
… requests. Since normal users are not trained or skilled experts, requests submitted by them are often informal natural language descriptions. Before … crowd. 2.2. Natural Language Processing in Software Requirements Engineering. One …

Addressing Complexities of Machine Learning in Big Data: Principles, Trends and Challenges from Systematical Perspectives
Q Wang, X Zhao, J Huang, Y Feng, J Su, Z Luo – 2017 – pdfs.semanticscholar.org
Page 1. Addressing Complexities of Machine Learning in Big Data: Principles, Trends and Challenges from Systematical Perspectives Qi Wang1, Xia Zhao*2, Jincai Huang1, Yanghe Feng1, Zhong Liu1, Jiahao Su3, Zhihao …

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper
G Luo – ACM SIGKDD Explorations Newsletter, 2017 – dl.acm.org
… seconds should have an indeterminate progress indicator [5]. So far, sophisticated, determinate progress indicators have been designed for automatic machine learning model selection [41, 46] and built for database queries [11, 37, 43-45], program compilation [42], static …

Hybrid Modeling of Cyber Adversary Behavior
A Sliva, S Guarino, P Weyhrauch, P Galvin… – … Conference on Social …, 2017 – Springer
… As a sociolinguistic theory, SFGs are widely used in seminal natural language processing (NLP) systems, such as Winograd’s language … We plan to explore various automated machine learning approaches that can augment part of this process, particularly in developing the …

Mining Domain-Specific Accounts for Scientific Contents from Social Media
J Wang, J Xiang, Y Zhang, K Uchino – International Conference on Web …, 2017 – Springer
… Our paper improves the handcrafted heuristic rules in [5] using an automated machine learning method with significantly higher … specific terms reflecting research interests, such as “machine learning”, “deep learning”, “artificial intelligence” and “natural language processing” can …

Active Learning with Visualization
L Huang – 2017 – dalspace.library.dal.ca
… ible speed. This affects automatic machine learning methods, especially supervised … tion of machine learning. Siri in Apple products is a well-known application that provides voice assistance for any operations with natural language processing inter- faces …

On the influence of dataset characteristics on classifier performance
T Gemert – 2017 – dspace.library.uu.nl
… Machine Learning is a largely independent sub field of Artificial Intelligence which has been widely used in areas such as computer-aided diagnosis, natural language processing, image classification, object recog- nition, etc …

Feature Engineering for Predictive Modeling using Reinforcement Learning
U Khurana, H Samulowitz, D Turaga – arXiv preprint arXiv:1709.07150, 2017 – arxiv.org
… common. Additionally, deep learning has mostly been successful with video, image, speech and natural language data, whereas the general numerical types of data encompasses a wide variety of domains and need FE. Our …

Understanding Hidden Memories of Recurrent Neural Networks
Y Ming, S Cao, R Zhang, Z Li, Y Chen, Y Song… – arXiv preprint arXiv …, 2017 – arxiv.org
… term memory (LSTM) networks and gated recurrent units (GRU), have been successfully applied in various natural language processing (NLP … a number of human-in-the-loop methods have been proposed as competitive replacements of full-automatic machine learning methods …

Adversarial Examples: Attacks and Defenses for Deep Learning
X Yuan, P He, Q Zhu, RR Bhat, X Li – arXiv preprint arXiv:1712.07107, 2017 – arxiv.org
… We show examples of selected applications from the field of reinforcement learning, generative modelling, face recognition, object detection, semantic segmentation, natural language processing, and malware … Then the target becomes a fully automatic machine learning system …

Relevance Mapping of Wikipedia Edits Using Semantic Web Concepts
P Gohil – 2017 – centralspace.ucmo.edu
… Automatic Machine Learning-based vandalism detection using Naïve Bayes and probabilistic sequence mapping classifiers have been studied widely. These methods combine natural language processing and machine learning and uses bag of words as it’s features to …

Mining API Aspects in API Reviews
G Uddin, F Khomh – 2017 – swat.polymtl.ca
… Both of these two constraints are solvable, but clearly can be chal- lenging for any automated machine learning classifier that aim to classify the sentences automatically. Benchmark overview. Figure 3 shows the overall distri- bution of the aspects in the benchmark …

The Impact of Sentiment Analysis Output on Decision Outcomes: An Empirical Evaluation
P Lak, O Turetken – AIS Transactions on Human-Computer …, 2017 – aisel.aisnet.org
… has also focused on going beyond supervised lexicon development to semi-automatic and automatic machine learning approaches (Bai … Lexalytics identifies these sentiment-bearing words and phrases through a well-known natural language processing technology called parts …

Addressing structural and linguistic heterogeneity in the Web
J Rouces, G de Melo, K Hose – AI Communications – content.iospress.com
… Currently, there are several third-party systems that extract FrameBase-modelled knowledge from natural language [2,11], but these are restricted to source texts provided in the … There has also been work on automatic machine learning-based translations of FrameNet [12] …

Evaluation Of A Factual Claim Classifier With And Without Using Entities As Features
AAA Syed – 2017 – uta-ir.tdl.org
… We briefly include a few. • The mechanism they employ. NER tools range from manually specified systems (eg grammar rules) to fully automatic machine-learning processes. • They utilize different classes ie entity types. • Outputted data are of different formats …

Vertical Ensemble Co-Training for Text Classification
G Katz, C Caragea, A Shabtai – ACM Transactions on Intelligent Systems …, 2017 – dl.acm.org
Page 1. 21 Vertical Ensemble Co-Training for Text Classification GILAD KATZ, Ben-Gurion University of the Negev CORNELIA CARAGEA, University of North Texas ASAF SHABTAI, Ben-Gurion University of the Negev High-quality …

Applying named entity recognition and co-reference resolution for segmenting English texts
P Fragkou – Progress in Artificial Intelligence, 2017 – Springer
… Effective natural language processing systems and text segmentation tools usually operate on text in specific domains and sources … methods they rely upon range from completely manually specified systems (eg, grammar rules) to fully automatic machine learning processes, not …

A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse
J Kalyanam, TK Mackey – Current Addiction Reports, 2017 – Springer
… API application program interface, ML machine learning, M million, NLP natural language processing, K thousand, GIS geographic … In the first category of machine learning strategies, several researchers employed automated machine learning techniques to analyze large …

Workshop Program
A ANANDKUMAR, FEI SHA – 2017 – pdfs.semanticscholar.org
… Learning for Autonomous Vehicles 2017 Li, Urtasun, Gray, Savarese C4.11, Learning to Generate Natural Language Miao, Ling … Workshop on Human Interpretability in Machine Learning (WHI) Varshney, Weller, Kim, Malioutov C4.9, Automatic Machine Learning (AutoML 2017 …

Schedule Highlights
P Sturm – Machine Learning, 2017 – pdfs.semanticscholar.org
… 12, 19, 24, 33]. These works have drawn inspiration from and made significant contributions to areas of machine learning as diverse as learning on graphs to models in natural language processing. Recent advances enabled …

Early Stage Malware Prediction Using Recurrent Neural Networks
M Rhode, P Burnap, K Jones – arXiv preprint arXiv:1708.03513, 2017 – arxiv.org
… Recurrent models have been employed successfully in the fields of natural language processing (NLP) and can be used to predict and generate text based on an initial short sequence of words or characters [13] or an image [23] …

A Fuzzy Load Balancer for Adaptive Fault Tolerance Management in Cloud Platforms
H Arabnejad, C Pahl, G Estrada, A Samir… – European Conference on …, 2017 – Springer
… For us, it allows multiple possibly conflicting options – whether arising from an automated (machine) learning approach as multiple options or provided by different experts [3] – to be joined into a … A linguistic variable is a variable whose values are words in a natural language …

A Fuzzy Load Balancer for Adaptive Fault Tolerance Management in Cloud Platforms
F Fowley – Service-Oriented and Cloud Computing: 6th IFIP WG …, 2017 – Springer
… For us, it allows multiple possibly conflicting options–whether arising from an automated (machine) learning approach as multiple options or provided by different experts [3]–to be joined into a … A linguistic variable is a variable whose values are words in a natural language …

Crosslinguistic Influence and Distinctive Patterns of Language Learning: Findings and Insights from a Learner Corpus
A Golden, S Jarvis, K Tenfjord – 2017 – books.google.com
Page 1. Second Language Acquisition – Crosslinguistic influence and Distinctive Patterns of Language Learning Findings and Insights from a Learner Corpus Edited by Anne Golden, Scott Jarvis and Kari?enfjord Page 2. Crosslinguistic …

AOGNets: Deep AND-OR Grammar Networks for Visual Recognition
X Li, T Wu, X Song, H Krim – arXiv preprint arXiv:1711.05847, 2017 – arxiv.org
… This is a 1-D special case of the method presented in [33, 39]. It can also be understood as a modified version of the well-known Cocke-Younger- Kasami (CYK) parsing algorithm in natural language pro- cessing according to a binary composition rule …

Changing Jobs: The Fair Go in the New Machine Age
M Quigley, J Chalmers – 2017 – books.google.com
… recent feats in AI. In 2011 IBM’s ‘Watson’ – a computer system designed specifically for answering questions in natural language – beat the two reigning champions in the general knowledge quiz show Jeopardy! In 2012 a prediction …

Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes
R Liu, MDM AbdulHameed… – Journal of chemical …, 2017 – ACS Publications
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Discovering a Domain Knowledge Representation for Image Grouping: Multimodal Data Modeling, Fusion, and Interactive Learning
X Guo – 2017 – search.proquest.com
… 12. 2.2.2 Natural language and domain knowledge . . . . . 13 … multiword expressions, which can be used for further analysis and modeling. 2.2.2 Natural language and domain knowledge. Language is the primary conduit to express meaning. Our diagnostic verbal …

A social media based index of mental well-being in college campuses
S Bagroy, P Kumaraguru… – Proceedings of the 2017 …, 2017 – dl.acm.org
… 60]. We extend this body of work by developing an automated machine learning method that can detect mental health expressions in social media, specifically in the context of college student populations. College Students …

Artificial Intelligence in Finance: Forecasting Stock Market Returns Using Artificial Neural Networks (Available on Internet)
A Zavadskaya – 2017 – helda.helsinki.fi
… and machine learning. Artificial Intelligence has progressed dramatically and nowadays most popular areas of its application are speech recognition, natural language processing, image recognition, sentiment analysis, autonomous driving, and robotics. (Pannu, 2015) …

Quantitative text analysis of policy uncertainty: FDI and trade of Ukrainian manufacturing firms
O Shepotylo, J Stuckatz – 2017 – papers.ssrn.com
Page 1. Electronic copy available at: https://ssrn.com/abstract=2983695 Quantitative text analysis of policy uncertainty: FDI and trade of Ukrainian manufacturing firms Oleksandr Shepotylo and Jan Stuckatz? June 9, 2017 Abstract …

Exploratory investigation into the practice of communicating to publics using English as a Lingua Franca (ELF) by Finnish companies
D Ingram – 2017 – muep.mau.se
… reach their publics. This indicates that an often-subconscious translation or remediation of messaging is made from the ELF-originated message to the recipient’s strongest and most natural language and any further outward communication may go through a similar process …

Asset returns, news topics, and media effects
VH Larsen, LA Thorsrud – 2017 – papers.ssrn.com
… rules for classifying the news, our approach utilizes a fully automated machine learning algorithm … than a million unique tokens. This massive amount of data makes statistical computa- tions challenging, but as is customary in the natural language processing literature some …

Asset returns, news topics and media effects
V Høghaug Larsen, LA Thorsrud – 2017 – brage.bibsys.no
… rules for classifying the news, our approach utilizes a fully automated machine learning algorithm … than a million unique tokens. This massive amount of data makes statistical computa- tions challenging, but as is customary in the natural language processing literature some …

Towards a science of human stories: using sentiment analysis and emotional arcs to understand the building blocks of complex social systems
AJ Reagan – 2017 – search.proquest.com
… Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a “big data” lens … understanding of human behavior. Advances in computing power, natural language processing, and …

Sequential Resource Allocation Under Uncertainty: An Index Policy Approach
W Hu – 2017 – search.proquest.com
Sequential Resource Allocation Under Uncertainty: An Index Policy Approach. Abstract. We consider a class of stochastic sequential allocation problems – restless multi-armed bandits (RMAB) with a finite horizon and multiple pulls per period …

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