NLTK & Natural Language Generation 2017


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A review of natural language processing techniques for opinion mining systems
S Sun, C Luo, J Chen – Information Fusion, 2017 – Elsevier
Skip to main content …

A novel approach for automatic text analysis and generation for the cultural heritage domain
F Piccialli, F Marulli, A Chianese – Multimedia Tools and Applications, 2017 – Springer
… MWN, MultiWordNet, 2015, http://multiwordnet.fbk.eu/. 21. NLTK, Natural Language Toolkit, 2015, http://www.nltk.org/. 22 … ISBN: 978-953-51-0597-8, InTechGoogle Scholar. 23. Reiter E, Dale R (1997) Building applied natural language generation systems …

Learning to generate one-sentence biographies from Wikidata
A Chisholm, W Radford, B Hachey – arXiv preprint arXiv:1702.06235, 2017 – arxiv.org
… We select all enti- ties that are INSTANCE OF human in Wikidata. We then use sitelinks to identify each entity’s Wikipedia article text and NLTK (Bird et al., 2009) to tokenize and extract the lower-cased first sen- tence. This results in 1,268,515 raw knowledge- text pairs …

GuessWhat?! Visual object discovery through multi-modal dialogue
H De Vries, F Strub, S Chandar, O Pietquin… – Proc. of …, 2017 – openaccess.thecvf.com
… Finally, the embedding of the current natural language question q is computed using an Long Short-Term Memory (LSTM) network [15] where questions are first tokenized by using the word punct tokenizer from the python nltk toolkit [7]. For simplicity, we decided to ignore the …

A Joint Model for Question Answering and Question Generation
T Wang, X Yuan, A Trischler – arXiv preprint arXiv:1706.01450, 2017 – arxiv.org
… URL http://arxiv.org/abs/1409.0473. Bird, Steven. Nltk: the natural language toolkit. In Pro- ceedings of the COLING/ACL on Interactive presenta- tion sessions, pp. 69–72 … In The 9th International Natural Language Generation conference, pp. 217, 2016 …

Mapping natural language to description logic
B Gyawali, A Shimorina, C Gardent… – European Semantic …, 2017 – Springer
… The parser and the generator exploit the grammar and the lexicon to map natural language to OWL DL formulae (semantic parsing) and OWL DL formulae to natural language (generation and more specifically, surface realisation … 3. We use the NLTK regular expression chunker …

Natural language processing
K Sirts – 2017 – courses.cs.ut.ee
… The goal is to get experience with some of the tools frequently used for NLP • NLTK (general text processing) • Gensim (word embeddings, topic models) • Log-?linear models/CRF … Machine translation • Natural language generation • Text summarization • Dialog systems 23 …

Extractive Based Automatic Text Summarization.
SM Patel, VK Dabhi, HB Prajapati – JCP, 2017 – jcomputers.us
… The abstract based summarization is quite difficult to generate because of machines limitation and also it’s a part of Natural Language Generation … 2.2.3. Natural language toolkit (NLTK) NLTK [17] is python based toolkit for natural language processing …

Tensor Product Generation Networks
Q Huang, P Smolensky, X He, L Deng, D Wu – arXiv preprint arXiv …, 2017 – arxiv.org
… proportion conforming. We use the Natural LanguageToolkit [13] to identify the part of speech of each word in the captions. (Since NLTK does not distinguish prepositions from conjunctions, we merge their statistics. Note that …

Bibi system description: Building with cnns and breaking with deep reinforcement learning
Y Li, T Cohn, T Baldwin – Proceedings of the First Workshop on Building …, 2017 – aclweb.org
… results of our preliminary experiments 1. Empirically, this can be attributed to the difficulty of defining an order over a natu- ral language token set, as well as the non-convex nature of the semantic space in natural language generation … NLTK: The natural language toolkit …

A hybrid (visual/natural) controlled language
Y Haralambous, J Sauvage-Vincent… – Language Resources and …, 2017 – Springer
… T}\) are filtering applications providing the contents of the visual sentence and of the textual sentence; “analysis” means obtaining semantics through the synthetic bottom-up approach of semantic attributes of the syntax tree; “nlg” means Natural Language Generation, and “vlg …

A Study on Natural Language Processing for Human Computer Interaction
N MPSTME – ijarcet.org
… [Online] Available: http://www.nltk.org/book … Majed Bokhari, Pavan Mhasavekar, “USING A NATURAL LANGUAGE GENERATION APPROACH TO DOCUMENT SIMULATION RESULTS”, Proceedings of the 2013 Winter Simulation Conference, Beaumont, TX 77710, USA [22 …

Python Natural Language Processing: Advanced machine learning and deep learning techniques for natural language processing
J Thanaki – 2017 – dl.acm.org
… Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford Core NLP and so on Learn about Features Extraction and Feature selection as part of … Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems …

Computational models for text summarization
L Keselman, L Schubert – leonidk.com
… combining different ways of tracking important concepts in articles and using a variety of natural language generation models to create … Available: https://www.kaggle.com/benhamner/ nips-papers [15] E. Loper and S. Bird, “Nltk: The natural language toolkit,” in Proceedings …

Enable Smart Farm in Digital India with Artificial Intelligence and IoT
MTD Ganesh – Imperial Journal of Interdisciplinary …, 2017 – imperialjournals.com
… on signal processing, syntactic analysis, discourse analysis semantic analysis, pragmatics thereby enabling the Natural Language Generation for more … As an alternate the following open source platform viz, Stanford’s Core NLP Suite, Natural Language Toolkit, Apache Lucene …

Leveraging Tokens in a Natural Language Query for NLIDB Systems
A Palakurthi – 2017 – pdfs.semanticscholar.org
… English. NLIDB systems use Natural Language Generation (NLG) modules to provide answers in the form of sentences. It … user. It could be generated based on templates or by using natural language generation techniques. 6 …

Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation Through a Human Creativity Test
YSA Rebolledo, P van der Putten… – … on Evolutionary and …, 2017 – Springer
… of the 12th International Society for Music Information Retrieval Conference (2011)Google Scholar. 2. Bird, S.: NLTK: the natural language toolkit … Van Deemter, K., Krahmer, E., Theune, M.: Real versus template-based natural language generation: a false opposition …

Statistical Language Models applied to News Generation
JRP Soares – 2017 – repositorio-aberto.up.pt
… 2 2 Natural Language Generation 5 2.1 HistoricalReview . . . . . 5 … 18 2.6.1 Natural Language Toolkit (NLTK) . . . . 18 2.6.2 NaturalOWL …

Sentiment Analysis of English Literature using Rasa-Oriented Semantic Ontology
D Sreejith, MP Devika, NS Tadikamalla… – Indian Journal of Science …, 2017 – indjst.org
… NLP consists of several researched tasks like Machine Translation, Natural Language Generation, Morphological Segmentation, Part-of-Speech Tagging, Parsing, Sentiment Analysis etc1. Sentiment Analysis is, at present, widely … NLTK (Natural Language Tool Kit) library …

The Impact of Personalisation on Human-Robot Interaction in Learning Scenarios
N Churamani, P Anton, M Brügger… – Proceedings of the 5th …, 2017 – dl.acm.org
… The language module consists of four compo- nents (see Figure 4) namely, Natural Language Understanding – Named Entity Recognition, Dialogue Management, Knowl- edge Base and Natural Language Generation. Natural …

A Rule-Based Decision Support System for Authoring Technical Instructions
RS Renu, L Hanson – ASME 2017 …, 2017 – … .asmedigitalcollection.asme.org
… Limitations [21] Natural language generation High software … 6. DECISION SUPPORT SYSTEM The decision support system, developed in Python, uses two publically available natural language processing tools: Textstat [30] and Natural Language Toolkit (NLTK) [26] …

Challenges in data-to-document generation
S Wiseman, SM Shieber, AM Rush – arXiv preprint arXiv:1707.08052, 2017 – arxiv.org
Page 1. arXiv:1707.08052v1 [cs.CL] 25 Jul 2017 Challenges in Data-to-Document Generation Sam Wiseman and Stuart M. Shieber and Alexander M. Rush School of Engineering and Applied Sciences Harvard University Cambridge …

Native Language Identification of Spoken Language Using Recurrent Neural Networks
KC Huang, J Lu, W Lu – stanford.edu
… Wen et al. (2015) discusses natural language generation (NLG) which is used to represent the persona of a system, impacting a users … In addition, we use the Python Natural Language Toolkit (NLTK) to automatically ap- ply part-of-speech tags with the Penn Treebank Tagset …

A Review of Text Mining Techniques & Applications
K Sharma, A Sharma, D Joshi, N Vyas… – International Journal of …, 2017 – ijcjournal.org
… Semantic Based Approach: In Semantic support approach on the other hand, semantic depiction of text is used as input into natural language generation (NLG) system. This system focus on recognizing the … [14] Steven Bird. “NLTK: The Natural Language Toolkit”, Proc …

Extracting Information from Social Network using NLP
C Virmani, A Pillai, D Juneja – International Journal of …, 2017 – ripublication.com
… tagging, named entity extraction, translation, information grouping, natural language generation, feedback analysis and more. It provides a command line interface with some predefined models where models are trained and evaluated. • Natural Language Toolkit (NLTK): It is a …

A Research Review On Comparative Analysis Of Data Mining Tools, Techniques And Parameters
A Sharma, B Kaur – International Journal of Advanced …, 2017 – search.proquest.com
… P.Ohl, C.Sieb, K.Thiel and B.Wiswedel,”KNIME: The. Konstanz Information Miner,”Springer,2008. [39] E.Loper and S.Bird ,”NLTK: The Natural Language. Toolkit,”2002. [40] Z.Haofeng,”RapidMiner: A Data Mining Tool Based on. Association Rules,” Springer,2001 …

Intelligent Personal Assistant with Knowledge Navigation
A Kumar, R Dutta, H Rai – arXiv preprint arXiv:1704.08950, 2017 – arxiv.org
… This process (lemmatization) can be performed using WordNet corpora from NLTK in Python very easily … Reinforcement learning for adaptive dialogue systems: A data-driven methodology for dialogue management and natural language generation. Springer …

Learning to generate product reviews from attributes
L Dong, S Huang, F Wei, M Lapata, M Zhou… – Proceedings of the 15th …, 2017 – aclweb.org
… The dataset is available at https://goo.gl/TFjEH4. 4.2 Settings We used NLTK (Bird et al., 2009) to tokenize the reviews, and employed the Wikipedia list of com- mon misspellings to correct misspelled words. We kept words that appeared more than 10 times in our vocabulary …

Learning concepts through conversations in spoken dialogue systems
R Jia, L Heck, D Hakkani-Tür… – Acoustics, Speech and …, 2017 – ieeexplore.ieee.org
… We use a predefined list of stopwords from NLTK [21], combined with a few additional words (eg “restaurant”) that are not semantically important in our particular … Much future work remains to improve our system, beginning with the problem of natural language generation (NLG) …

Automatic Summarization of Online Debates
N Sanchan, A Aker, K Bontcheva – arXiv preprint arXiv:1708.04587, 2017 – arxiv.org
… 9The measurement is performed using nltk metrics, http://www.nltk.org/api/nltk.metrics.html. Page 6 … In INLG 2016 – Proceedings of the Ninth Inter- national Natural Language Generation Confer- ence, September 5-8, 2016, Edinburgh, UK. pages 61–69 …

Writing Style Conversion using Neural Machine Translation
SW Jang, J Min, M Kwon – pdfs.semanticscholar.org
… We utilized a widely-used, standard BLEU score[8] scheme implemented in Python nltk library … Grammar as a Foreign Language, Proceedings of Neural Information Pro- cessing Systems 2014. 9 Page 10. [3] Stylistic Transfer in Natural Language Generation Systems Using …

Implementation of a Bangla chatbot
TD Orin – 2017 – dspace.bracu.ac.bd
… Page 25. Golpo: Implementation of a Bangla Chatbot 25 3.4.1 Environmental Setup Natural Language Processing (NLP) techniques such as Natural Language Toolkit (NLTK) for Python can be applied to analyze speech, and intelligent responses can be found by …

Performance analysis of keyword extraction algorithms assessing extractive text summarization
A Kumar, A Sharma, S Sharma… – Computer …, 2017 – ieeexplore.ieee.org
… brings in whole new class of techniques which instead of using the exact sentences from the original text rather rely on generating its own sentences or natural language generation (NLG) … We use the Porter2 English Snowball [12] stemmer provided by the NLTK [13] library …

Zero-Shot Style Transfer in Text Using Recurrent Neural Networks
K Carlson, A Riddell, D Rockmore – arXiv preprint arXiv:1711.04731, 2017 – arxiv.org
… The problem of stylistic paraphrasing is clearly relevant for the creation of natural language generation systems … verse numbers at the beginning of each line were removed and then each of the three sets (development, testing, training) was tokenised using the nltk package in …

Computational Linguistic Creativity: Poetry generation given visual input
M Loller-Andersen – 2017 – brage.bibsys.no
… Page 4. Page 5. Abstract Poetry is one of the most complex Natural Language Generation (NLG) tasks, because the value of poetry is very dependent of both the form and content … 23 2.5.3. Natural Language ToolKit . . . . . 24 3. Related Work 27 …

Summarization Of Software Artifacts: A Review
S Gupta, SK Gupta – aircconline.com
… 167 various open source NLP toolsavailable for pre-processing of corpus like python NLTK, Apache OpenNLP, Stanford CoreNLP, etc … 174 In Semantic Based Approach, semantic information about the document is used and is fed into the Natural Language Generation system …

Sentiment Analysis of Moroccan Tweets using Naive Bayes Algorithm
A EL ABDOULI, L HASSOUNI, H ANOUN – academia.edu
… The other is Natural Language Generation (NLG) translate information from computer databases into readable human language … The library used to preprocess tweets with NLP is the Natural language processing Toolkit (NLTK) [9], which is a set of open-source Python modules …

Self-Guiding Multimodal LSTM-when we do not have a perfect training dataset for image captioning
Y Xian, Y Tian – arXiv preprint arXiv:1709.05038, 2017 – arxiv.org
… The third group of approaches integrates image under- standing and natural language generation into a unified pipeline … Images without valid descriptions are dis- carded. We perform a light pre-processing utilizing NLTK 8 Page 9 …

Mining tweets of Moroccan users using the framework Hadoop, NLP, K-means and basemap
A El Abdouli, L Hassouni… – 2017 Intelligent Systems …, 2017 – ieeexplore.ieee.org
… The other is Natural Language Generation (NLG) that transforms a formal meaning representation into text that expresses that meaning … The library used in our system to process tweets with NLP is the Natural language processing Toolkit (NLTK), which is a set of open-source …

Automatic Neural Question Generation using Community-based Question Answering Systems
T Baghaee – 2017 – uleth.ca
Page 1. AUTOMATIC NEURAL QUESTION GENERATION USING COMMUNITY- BASED QUESTION ANSWERING SYSTEMS TINA BAGHAEE Bachelor of Science, Shahid Beheshti University, 2011 A Thesis Submitted to the …

Syntactic and semantic features for human like judgement in spoken CALL
A Magooda, D Litman – Proc. 7th ISCA Workshop on Speech and … – regulus.unige.ch
… To check for spelling mistakes we use the NLTK English spell checker [16] … pilot shared task,” in Proceedings of the 13th European Workshop on Natural Language Generation … E. Loper, Natural language processing with Python: analyzing text with the natural language toolkit …

Robot perception errors and human resolution strategies in situated human–robot dialogue
N Schütte, B Mac Namee, J Kelleher – Advanced Robotics, 2017 – Taylor & Francis
… Proceedings of the 10th European Workshop on Natural Language Generation (ENLG) … The basic natural language processing pipeline of the Toy Block system involves: (1) parsing the user input (using the NLTK parser [19 Manning C, Surdeanu M, Bauer J, et al …

Improving the Memory of Intelligent Personal Assistants
LJ Peter – 2017 – researchgate.net
… language understanding approaches to enhance web search relevance, neural networks to reduce the cost of cooling their data centers, natural language generation functions to translate one … management unit (DM), and (3) natural language generation unit (NLG) …

Automatic labeling of continuous wave Doppler images based on combined image and sentence networks
M Moradi, Y Guo, Y Gur… – … Imaging (ISBI 2017) …, 2017 – ieeexplore.ieee.org
… one of the most popular automated, effi- cient, and inexpensive metrics for machine translation natural language generation evaluation. Our use of the BLEU score is a new application for this classic measure. We used the open source implementation through NLTK [11] for …

Deep Memory Networks for Natural Conversations
??? – 2017 – s-space.snu.ac.kr
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The case for being average: A mediocrity approach to style masking and author obfuscation
G Karadzhov, T Mihaylova, Y Kiprov… – … Conference of the Cross …, 2017 – Springer
… To do this, we first segmented the text into sentences using the NLTK sentence splitter … doi:10.1007/978-3-642-24212-0_9 CrossRefGoogle Scholar. 10. Kabbara, J., Cheung, JCK: Stylistic transfer in natural language generation systems using recurrent neural networks …

Grammar rules for the isiZulu complex verb
CM Keet, L Khumalo – Southern African Linguistics and Applied …, 2017 – Taylor & Francis
… Regarding controlled natural languages and natural language generation, there are only two recent papers (Keet and Khumalo 2014a; 2014b), which cover verbs only to the extent of noun class-appropriate singular present tense when verbalising simple existential …

Ask Me Otherwise: Synonym-Based Memory Networks for Reading Comprehension
B Srivatsan – bharathsrivatsan.com
… I ignored words from synsets not already present in the dictionary D (as that would mean they were certainly not in the input memories). The implementation of WordNet I used was rolled into the Natural Language Toolkit (NLTK) package, provided for Python. 3.3.2 Word2Vec …

Neural Sequence-Labelling Models for Grammatical Error Correction
H Yannakoudakis, M Rei, ØE Andersen… – Proceedings of the 2017 …, 2017 – aclweb.org
… (2016), who perform supervised N-best list re-ranking using a large set of features, and further extend their ap- proach to generate new hypotheses (NUS16SMT + re-ranker).5 4The differences are likely to be caused by different ver- sions of the NLTK tokeniser and/or Moses …

Training end-to-end dialogue systems with the ubuntu dialogue corpus
RT Lowe, N Pow, IV Serban, L Charlin… – Dialogue & …, 2017 – dad.uni-bielefeld.de
… More advanced methods could consider some way to approximate this ordinal information, such that a neural network model could be explicitly trained as a ranking system; however, this is beyond the scope of this paper. 7. www.nltk.org/ 8. http://www.ark.cs.cmu.edu/TweetNLP …

The Case for Being Average: A Mediocrity Approach to Style Masking and Author Obfuscation
G Georgiev, I Koychev, P Nakov – Experimental IR Meets …, 2017 – books.google.com
… To do this, we first segmented the text into sentences using the NLTK sentence splitter … Springer, Heidelberg (2011). doi: 10.1007/978-3-642-24212-09 Kabbara, J., Cheung, JCK: Stylistic transfer in natural language generation sys- tems using recurrent neural networks …

Fire detection and incidents localization based on public information channels and social media
KG Thanos, K Skroumpelou… – … Fusion, and Target …, 2017 – spiedigitallibrary.org
… main topics of Natural Language Processing are: Learning syntactic and semantic rules, Determine concept, topics and sentiment from a document, automatics summarization, machine translation, Natural Language generation, information extraction … Note: Python NLTK 3.0 Part …

Evaluating the Reliability and Interaction of Recursively Used Feature Classes for Terminology Extraction
A Hätty, M Dorna, SS im Walde – … of the Student Research Workshop at …, 2017 – aclweb.org
… Terms are linguistic units which characterize a specific topic domain. For example, in the area of Computational Linguistics Parsing, Machine Translation and Natural Language Generation are candidates for single and multi-word terms … (2010) and the nltk- documentation 4 …

Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples
P Vougiouklis, H Elsahar, LA Kaffee, C Gravier… – arXiv preprint arXiv …, 2017 – arxiv.org
… In the context of the Semantic Web, Natural Language Generation (NLG) is concerned with the im- plementation of textual interfaces that would effectively increase … Each Wikipedia summary is tokenised and split into sentences using the Natural Language Toolkit (NLTK) [29] …

Dissertations in Forestry and Natural Sciences
EA KOLOG – epublications.uef.fi
… NLG Natural Language Generation NLU Natural Language Understanding NLP Natural Language Processing NLTK Natural Language Tool Kit NRC National Research Council Ghana PAD Pleasure, Arousal and Dorminance PD Participatory Design POS Part-Of-Speech RQ …

Semantic Analysis for Human Motion Synthesis
??? – 2017 – s-space.snu.ac.kr
… Page 24. 2: Background 16 Natural language generation is the task of generating natural language from machine rep- resentation … readable text based on sales data [4].Advancement of deep learning technology has affected also natural language generation …

Evaluation of Modern Tools for an OMSCS Advisor Chatbot
E Gregori – 2017 – smartech.gatech.edu
… In most systems the user interface is a web page. The natural language section is made up of the natural language processing (NLP) block and natural language generation (NLG) block … NLTK http://www.nltk.org Python library tokenize, tag, entities …

Variational Deep Semantic Hashing for Text Documents
S Chaidaroon, Y Fang – arXiv preprint arXiv:1708.03436, 2017 – arxiv.org
Page 1. arXiv:1708.03436v1 [cs.IR] 11 Aug 2017 Variational Deep Semantic Hashing for Text Documents Suthee Chaidaroon Department of Computer Engineering Santa Clara University Santa Clara, CA 95053, USA schaidaroon@scu.edu …

Towards the Implementation of an Intelligent Software Agent for the Elderly
AHF Dinevari – 2017 – era.library.ualberta.ca
… 64 6 Response Generation 65 6.1 Natural Language Generation … ML Machine Learning. MUC Machine Understanding Conference. NLG Natural Language Generation. NLP Natural Language Processing. NLU Natural Language Understanding …

A deep reinforcement learning chatbot
IV Serban, C Sankar, M Germain, S Zhang… – arXiv preprint arXiv …, 2017 – arxiv.org
… The system consists of an ensemble of natural language generation and retrieval models, including template-based models, bag-of-words models, sequence-to-sequence neural network and latent variable … If that fails, Evibot applies NLTK’s named entity processor (Bird et al …

Methods of sentence extraction, abstraction and ordering for automatic text summarization
MT Nayeem – 2017 – uleth.ca
Page 1. METHODS OF SENTENCE EXTRACTION, ABSTRACTION AND ORDERING FOR AUTOMATIC TEXT SUMMARIZATION MIR TAFSEER NAYEEM Bachelor of Science, Islamic University of Technology, 2011 A Thesis …

A Question Answering System Design about the Holy Quran
BIO Hamoud – 2017 – repository.sustech.edu
… KDT Knowledge-Discovery in Text NER Named Entity Recognition NLP Natural Language Processing nltk natural language toolkit Q&A Question and Answer QA Question Answering QAEQAS Quranic Arabic English Question Answering System SVM Support Vector Machine …

Case Study: The Manually Annotated Sub-Corpus
N Ide – Handbook of Linguistic Annotation, 2017 – Springer
… input and/or output annotations in GrAF format; a “CAS Consumer” to enable using GrAF annotations in the Unstructured Information Management Architecture (UIMA) [9]; and a corpus reader for importing MASC data and annotations into the Natural Language Toolkit (NLTK) …

Harnessing rhetorical figures for argument mining
J Lawrence, J Visser, C Reed – Argument & Computation, 2017 – content.iospress.com
… Grasso [17] develops these starting points further, with a particular view to building natural language generation systems that make explicit use of insights from rhetoric … For each individual turn, we use the Python Natural Language Toolkit (nltk.org) Porter Stemmer to determine …

Controversy detection in Wikipedia using semantic dissimilarity
MZ Jhandir, A Tenvir, BW On, I Lee, GS Choi – Information Sciences, 2017 – Elsevier
… The various approaches to natural language processing include, but are not limited to 8 text preprocessing, lexical analysis, syntactic parsing, semantic analysis, natural language generation, corpus creation, treebank annotation, part-of-speech tagging, statistical parsing, and …

A Unified Latent Variable Model for Contrastive Opinion Mining
E IBEKE, LIN Chenghua, A Wyner… – Frontiers of Computer …, 2017 – researchgate.net
… 1) http://www.gallup.com/poll/126521/favor-oppose-obama-healthcare- plan.aspx 2) https://github.com/eibeke/El-Capitan-Dataset 3) NB: the remaining 7% neutral responses are ignored. 4) http://www.nltk.org/ Page 8. Front. Comput. Sci. 7 Table 2 Dataset statistics. <f

Text Mining in Financial Industry: Implementing Text Mining Techniques on Bank Policies
D Ferati – 2017 – dspace.library.uu.nl
… LSA Latent Semantic Analysis MAM Meta-Algorithmic Model MUC Message Understanding Conference NE Named Entity NER Named Entity Recognition NLIP Natural Language Input Processing NLP Natural Language Processing NLTK Natural Language Toolkit P Precision …

Learning Generative End-to-end Dialog Systems with Knowledge
T Zhao – 2017 – cs.cmu.edu
… NLG Natural Language Generation NLP Natural Language Processing … Furthermore, although out of the scope of this thesis, the methods developed here can be also applied to related conditional natural language generation tasks, eg image captioning or question-answering …

Dialogue Act Recognition for Conversational Agents
LE Hacquebord – 2017 – dspace.library.uu.nl
… Page 11. xi List of Abbreviations NLP Natural Language Processing NLU Natural Language Understanding NLG Natural Language Generation DM Dialogue Manager SRL Semantic Role Labelling pp Percentage Point(s) Page 12. Page 13. 1 Chapter 1 Introduction …

From Event to Story Understanding
N Mostafazadeh – 2017 – search.proquest.com
From Event to Story Understanding. Abstract. Building systems that have natural language understanding capabilities has been one of the oldest and the most challenging pursuits in AI. In this thesis, we present our research …

Using Syntactic Patterns to Enhance Text Analytics
BB Meyer – 2017 – search.proquest.com
… Computational linguistics, and specifically, the tools from Natural Language. Processing, are invaluable to research in sentiment analysis … Processing is equivalent to the role of reader/listener, while the task of Natural Language. Generation is that of the writer/speaker …

Exploring the Internal Statistics: Single Image Super-Resolution, Completion and Captioning
Y Xian – 2017 – search.proquest.com
Exploring the Internal Statistics: Single Image Super-Resolution, Completion and Captioning. Abstract. Image enhancement has drawn increasingly attention in improving image quality or interpretability. It aims to modify images …

Haskell Communities and Activities Report
M Maruseac, AS Mena, A Abel, A Granin, H Apfelmus… – 2017 – haskell.org
Index. Haskell Communities and Activities Report. http://tinyurl.com/haskcar. pdf version. Twenty-Seventh Edition – November 2014. Mihai Maruseac, Alejandro Serrano Mena (eds.). Andreas Abel. Alexander Granin. Heinrich Apfelmus. Emil Axelsson. Carl Baatz. Doug Beardsley …

An Algorithmic Approach to Personalized and Interactive News Generation
D Kim – 2017 – s-space.snu.ac.kr
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