Generative Text & Natural Language Processing


See also:

Generative Literature & Natural Language Processing | Procedural Generation & Natural Language Processing | Procedural Storytelling | Text Generation


Generative and discriminative text classification with recurrent neural networks
D Yogatama, C Dyer, W Ling, P Blunsom – arXiv preprint arXiv:1703.01898, 2017 – arxiv.org
… We focus on a simple NLP task—text classification—using discriminative and generative variant models based on a common neural network architecture … is its length in words, and it will predict a label y ? Y. We compare discrimina- tive and generative text classification models …

Expressionist: An authoring tool for in-game text generation
J Ryan, E Seither, M Mateas… – … Conference on Interactive …, 2016 – Springer
… Why have so few completed works of interactive storytelling featured generative text … Elsewhere we have argued that previous approaches to this challenge that have employed conventional techniques from natural language generation (NLG), though important, have …

Characters who speak their minds: Dialogue generation in Talk of the Town
J Ryan, M Mateas, N Wardrip-Fruin – Proc. AIIDE, 2016 – aaai.org
… of this content problem will rely on some amount of genera- tivity, and so natural language generation (NLG) appears as … grounds (Compton, Kybartas, and Mateas 2015)—whereas traditional NLG pipelines demand NLG expertise … Trac- ery: An author-focused generative text …

Linguistic structure prediction
NA Smith – Synthesis lectures on human language …, 2011 – morganclaypool.com
… In summary, then, this is a book about machine learning (ML), natural language processing (NLP), and computational … will lead to a paradigm change in ML and NLP, but at … Computational linguists who work on natural language generation may be frustrated by the emphasis on …

The user’s and the designer’s role and the aesthetic experience of generative literature
VC Pereira, C Maciel – Proceedings of the 12th Brazilian Symposium on …, 2013 – dl.acm.org
… On the other hand, studies on generative poetry have so far focused more on natural language processing and syntactic rules beneath verses than … Losh [15] analyzed different web text generators, which she called generative (text producers) and generic (obeying genre rules) …

A robust learning approach for text classification
V Ha-Thuc, P Srinivasan – Proceedings of the 7 SIAM Text Mining …, 2008 – researchgate.net
… Only the parts generated by t (the really relevant parts) contribute to the resulting distribution over words for topic t. And this distribution is the key parameter that needs to be learned in generative text classification methods ([9]). Therefore, the proposed approach is robust …

Semantic annotation aggregation with conditional crowdsourcing models and word embeddings
P Felt, E Ringger, K Seppi – Proceedings of COLING 2016, the 26th …, 2016 – aclweb.org
… Unfortunately, some text classification tasks make dis- tinctions for which no good generative text models currently exist, such as labeling the similarity … Empiricial Methods in Natural Language Processing (EMNLP 2014 … LREC Workshop on New Challenges for NLP Frameworks …

A model of text for experimentation in the social sciences
ME Roberts, BM Stewart, EM Airoldi – Journal of the American …, 2016 – Taylor & Francis

Scalable Text Mining with Sparse Generative Models
A Puurula – arXiv preprint arXiv:1602.02332, 2016 – arxiv.org
… A unifying formalization for generative text models is defined, bringing together research traditions … F1-score ML machine learning MNB Multinomial Naive Bayes NB Naive Bayes NDCG normalized discounted cumulative gain NLP natural language processing SVM Support …

Datatopia–Data Tracking in an Alternative world
Y Wang – portfolio.newschool.edu
… The stories are created with techniques of natural language processing and generative text. These techniques embody the comparison of algorithms versus subjectivity discussed in the relationships between us and our data …

Generation with Recurrent Neural Network
Y Hayashi, H Yanagimoto – … Informatics (IIAI-AAI), 2016 5th IIAI …, 2016 – ieeexplore.ieee.org
… The approach can generate a high quality abstract but needs more natural language processing techniques text understanding to construct an abstract and it includes unsolved problems. However, in these days, the automatic generative text summarization is realized with a …

Using Deep Learning to Improve the Accuracy of Requirements to Code Traceability
Y Zhao, TS Zaman, T Yu, JH Hayes – … of Traceability: The Next Ten Years, 2017 – arxiv.org
… Natural language generation using RNNs differ from text mining and retrieval systems; the gener- ated … We can then utilize the natural language processing method to obtain the mapping between code and its … As such, it is possible to train a generative text model based on the …

Estimating Reactions and Recommending Products with Generative Models of Reviews
J Ni, ZC Lipton, S Vikram, J McAuley – … on Natural Language Processing …, 2017 – aclweb.org
Proceedings of the The 8th International Joint Conference on Natural Language Processing, pages 783–791, Taipei, Taiwan, November 27 … In parallel, recent advances in generative text modeling have demonstrated the effectiveness of recurrent neural networks in capturing …

Text Transformation Via Constraints and Word Embedding
B Bay, P Bodily, D Ventura – ighth International Conference on …, 2017 – researchgate.net
… processing (NLP) and its subfield, natural language generation (NLG), address these problems. Syntactically correct text is available in abundance and is easily produced by humans. However, maintaining such syntactic correctness and semantic cohesion in generative text is …

Improving Filtering of Email Phishing Attacks by Using Three-Way Text Classifiers
A Trevino – 2012 – scholarsarchive.byu.edu
Page 1. Brigham Young University BYU ScholarsArchive All Theses and Dissertations 2012-03-13 Improving Filtering of Email Phishing Attacks by Using Three-Way Text Classifiers Alberto Trevino Brigham Young University – Provo …

Joint training of ratings and reviews with recurrent recommender networks
CY Wu, A Ahmed, A Beutel, AJ Smola – 2016 – openreview.net
… Neural Networks Neural networks have recently offered large improvements in natural language processing … This technique is common in NLP literature (Wang & McCallum, 2006) … Capturing meaning in product reviews with character-level generative text models. CoRR, 2015 …

Automatic Generation of Natural Language Explanations
F Costa, S Ouyang, P Dolog, A Lawlor – arXiv preprint arXiv:1707.01561, 2017 – arxiv.org
… Our empirical evaluation using natural language processing metrics shows the generated text’s quality is … demonstrated to show very good performance in natural language generation, since the … the automatic gen- eration of explanations, based on generative text reviews given …

WikidSimple: A Data-Driven Text Simplifier Using Tree Transducers Trained on Wikipedia
D Feblowitz – 2011 – cs.pomona.edu
… a grammar formalism expressive enough to capture the full range of these operations, we train a generative text simplification system … for assisting aphasic readers [CTAC00, CMC+98], generating sum- maries [Mah97, JM00], and preprocessing text for other NLP tasks [CS97] …

Business Applications of Deep Learning
A Vieira – Ubiquitous Machine Learning and Its Applications, 2017 – books.google.com
… APPLICATIONS TO NATURAL LANGUAGE PROCESSING Deep Learningishaving atremendousimpactin Natural Language Processing (NLP) … outperforming the best previous neural network NLP systems, and … good results for discriminative or generative text generation tasks …

Mapping annotations with textual evidence using an scLDA model
B Jin, V Chen, L Chen, X Lu – AMIA Annual Symposium …, 2011 – ncbi.nlm.nih.gov
… address this challenge has led to recent advances in biomedical natural language processing (BioNLP) and … classifier, it is encouraging because the latter is a generative text categorization classifier … be used to combine the syntactic information derived from NLP and semantic …

Improving Context Aware Language Models
A Jaech, M Ostendorf – arXiv preprint arXiv:1704.06380, 2017 – arxiv.org
… such as for LM personalization (Wen et al., 2013; Li et al., 2016), adapting an LM to different genres of tele- vision shows (Chen et al., 2015), adapting to long range dependencies in a document (Ji et al., 2015), sharing information in generative text classifiers (Yogatama et al …

Recurrent neural networks for modeling company-product time series
K Mirylenka, C Miksovic, P Scotton – Proceedings of AALTD, 2016 – aaltd16.irisa.fr
… appearances, such that state-of-the-art unsupervised techniques from Natural Language Processing (NLP) can be … of the state-of-the-art techniques for the tasks related to NLP … of unsupervised DNN, such as learning of word embeddings and generative text modeling using …

Analyzing Expressionist Grammars by Reduction to Symbolic Visibly Pushdown Automata
JC Osborn, J Ryan, M Mateas – 2017 – researchgate.net
… One account of these approaches is that they forego the power of conventional natural language generation pipelines to emphasize authorability and … to runtime concerns for procedural text, Short and Dias have individually articulated the need for generative text that expresses …

Learning to generate product reviews from attributes
L Dong, S Huang, F Wei, M Lapata, M Zhou… – Proceedings of the 15th …, 2017 – aclweb.org
Page 1. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 623–632, Valencia, Spain, April 3-7, 2017. cO2017 Association for Computational Linguistics …

On Suggesting Phrases vs. Predicting Words for Mobile Text Composition
KC Arnold, KZ Gajos, AT Kalai – … of the 29th Annual Symposium on User …, 2016 – dl.acm.org
… ACM Classification Keywords H.5.2 Information Interfaces: User Interfaces; I.2.7 Natural Language Processing … T., and Heck, L. Contextual LSTM (CLSTM) models for large scale NLP tasks … J. Capturing meaning in product reviews with character-level generative text models …

Grimes’ fairy tales: a 1960s story generator
J Ryan – International Conference on Interactive Digital …, 2017 – Springer
… these novel features, and what we know about the state of the art in the early 1960s, it would seem that Grimes’s system was among the most advanced natural language generation projects of … Compton, K., Kybartas, B., Mateas, M.: Tracery: an author-focused generative text tool …

Minimum description length modelling of musical structure
P Mavromatis – Journal of Mathematics and Music, 2009 – Taylor & Francis

Headline Generation with Recurrent Neural Network
Y Hayashi, H Yanagimoto – New Trends in E-service and Smart Computing, 2018 – Springer
… The approach can generate a favorable sentence but needs more natural language processing techniques to construct a sentence and it includes unsolved problems. However, in these days, the automatic generative text summarization is realized with a neural network …

Computational Creativity and Social Justice: Defining the Intellectual Landscape
G Smith – computationalcreativity.net
… Compton, K.; Kybartas, B.; and Mateas, M. 2015. Trac- ery: An Author-Focused generative text tool … ConceptNet 5: A large semantic network for relational knowledge. In The Peoples Web Meets NLP, Theory and Applications of Natural Lan- guage Processing …

Mining latent entity structures
C Wang, J Han – Synthesis Lectures on Data Mining and …, 2015 – morganclaypool.com
Page 1. Mining Latent Entity Structures Chi Wang Jiawei Han W ANG • HAN M IN IN G L A TE NT E NTIT Y S TR U C TU R E S MO R GAN & CL A YPOO L Jiawei Han, Lise Getoor, Wei Wang, Johannes Gehrke, Robert Grossman, Series Editors …

Grimes’ Fairy Tales: A 1960s Story Generator
EI Studio – … : 10th International Conference on Interactive Digital …, 2017 – books.google.com
… know about the state of the art in the early 1960s, it would seem that Grimes’s system was among the most advanced natural language generation projects of … Folklore 76 (302), 318–323 (1963) Compton, K., Kybartas, B., Mateas, M.: Tracery: an author-focused generative text tool …

Learning to re-rank: query-dependent image re-ranking using click data
V Jain, M Varma – Proceedings of the 20th international conference on …, 2011 – dl.acm.org
… Keyword-based image search is not only a problem of sig- nificant commercial importance but it also raises fundamen- tal research questions at the intersection of computer vision, natural language processing, machine learning, and … [30] learn a generative text model from the …

Controlling linguistic style aspects in neural language generation
J Ficler, Y Goldberg – arXiv preprint arXiv:1707.02633, 2017 – arxiv.org
… This work focuses on generating text while allowing control of its stylistic properties. The recent introduction of recurrent neural lan- guage models and recurrent sequence-to-sequence architectures to NLP brought with it a surge of work on natural language generation …

A Category Classification Algorithm For Indonesian And Malay News Documents
J Jaafar, Z Indra, N Zamin – JURNAL TEKNOLOGI, 2016 – researchgate.net
… information retrieval [7]. Other researcher [8], claimed that the task to perform TC requires multi-technique ie IR, Machine Learning, and Natural Language Processing at the … NB classifier is also known as a generative text classification since it generates a probabilistic model [21] …

Efficient exploration for dialogue policy learning with BBQ networks & replay buffer spiking
ZC Lipton, J Gao, L Li, X Li, F Ahmed… – arXiv preprint arXiv …, 2016 – arxiv.org
… fills in any vacant placeholders, yielding a structured representation such as inform(theater= Cinemark Lincoln Square), which is then translated by a natural language generation component to a … Capturing meaning in product reviews with character-level generative text models …

Incorporating Structural Bias into Neural Networks
Z Yang – 2017 – cs.cmu.edu
… to learn well. With the recent breakthrough of neural networks in computer vision [21] and natural language processing [40], feature representations can be learned directly in an end-to-end man- ner. Minimum human efforts …

Understanding Structured Documents with a Strong Layout
M Romeyn – thesisscientist.com
… classification and object detection challenges [15, 31, 28, 8]. The next great frontier in the search for artificial general intelligence (AGI), then, is Natural Language Processing (NLP). The quest to reach AGI is controversial. With public figures like Elon Musk and Steven Hawk …

Understanding Structured Documents with a Strong Layout
R Marc – 2017 – diva-portal.org
… classification and object detection challenges [15, 31, 28, 8]. The next great frontier in the search for artificial general intelligence (AGI), then, is Natural Language Processing (NLP). The quest to reach AGI is controversial. With public figures like Elon Musk and Steven Hawk …

Theognis of Megara and the Divine Creating Power in the Framework of Semiotic Textology: An Application of János Sándor Petöfi’s Theory to Archaic Greek …
M Giuffrè – Journal of Logic, Language and Information, 2012 – Springer
… and intersubjective controllability. In this monograph Petöfi formulated a generative text grammar, based on the conceptual and operational tools of logics (Textgrammatik mit nicht-linear festgelegter Textbasis). After the formulation …

Facilitating Corpus Annotation by Improving Annotation Aggregation
PL Felt – 2015 – search.proquest.com
Abstract. Annotated text corpora facilitate the linguistic investigation of language as well as the automation of natural language processing (NLP) tasks … automation of natural language processing (NLP) tasks. NLP tasks include problems such as spam …

Effective summarisation for search engines
L Leal Bando – 2013 – researchbank.rmit.edu.au
Page 1. Effective Summarisation for Search Engines A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Lorena Leal Bando BE, M.Sc, School of Computer Science and Information Technology, College of Science, Engineering and Health …

Explainable Recommendations
RC Kanjirathinkal – 2017 – cs.cmu.edu
Page 1. Thesis Proposal Explainable Recommendations Rose Catherine Kanjirathinkal November 2017 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Prof. William W. Cohen, Chair, Carnegie Mellon University Prof …

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Z Lipton, X Li, J Gao, L Li, F Ahmed, L Deng – arXiv preprint arXiv …, 2017 – arxiv.org
… This yields a structured representation such as inform(theater=Cinemark Lincoln Square), which is then mapped by a natural language generation module to a textual utterance, such as “This movie is playing tonight at Cinemark Lincoln Square.” The conversation process …

Efficient Exploration for Dialog Policy Learning with Deep BBQ Networks & Replay Buffer Spiking
ZC Lipton, J Gao, L Li, X Li, F Ahmed… – arXiv preprint arXiv …, 2016 – zacklipton.com
… The chosen action passes to the state tracker, which fills in any vacant placeholders, yielding a structured representation such as in- form(theater=Cinemark Lincoln Square), which is then translated by a natural language generation component to a textual utterance, such as …

Slant: A Blackboard System to Generate Plot, Figuration, and Narrative Discourse Aspects of Stories.
N Montfort, RP y Pérez, DF Harrell, A Campana – ICCC, 2013 – computationalcreativity.net
… GRIOT. This is a system that is the basis for interactive and generative text and multimedia works using Harrell’s Alloy algorithm for conceptual blending … 170 Page 4. cludes a standard three-stage natural language generation pipeline …

Automated Crowdturfing Attacks and Defenses in Online Review Systems
Y Yao, B Viswanath, J Cryan, H Zheng… – Proceedings of the 2017 …, 2017 – dl.acm.org
Page 1. Automated Crowdturfing Attacks and Defenses in Online Review Systems Yuanshun Yao ysyao@cs.uchicago.edu University of Chicago Bimal Viswanath viswanath@cs.uchicago.edu University of Chicago Jenna Cryan …

Emotion detection in blog posts using keyword spotting and semantic analysis
MJC Samonte, HIB Punzalan, RJPG Santiago… – Proceedings of the 3rd …, 2017 – dl.acm.org
… that the group got from the dictionary of WordNet [7]. WordNet is an open source software that is used for computational linguistics and natural language processing … According to Aggarwal, Naïve Bayes is the simplest and commonly used generative text classifiers [16] …

Literacy practices in an English language arts elective: An examination of how students respond to media literacy education
KE Garland – 2010 – search.proquest.com
… Practice and Methods. The New London Groups (NLG) concept of multiliteracies encompasses the multiple modes of texts one must be able to read and interpret and the varieties of literacy practices that one must draw upon in various social settings …

Deep learning based action recog-nition with application to dogs
W Zhao – 2017 – nada.kth.se
… neural network in 2012, deep learning has been further successfully applied to many areas including visual object recognition[22, 23, 24], Natural Language Processing[25, 26, 27], Speech recognition[28, 29]and many other domains such as drug discov- ery and genomics …

Property ranking approaches for semantic web browsers-a review of ontology property ranking algorithms
F Paul – 2014 – dspace.ou.nl
… method that examines the ontology structure. The text-driven algorithms were inspired partly by other works and partly through research in the field of Natural Language Processing (NLP) 12. Our research aimed to help bridge …

An Emerging Canon? A Preliminary Analysis of All References to Creative Works in Critical Writing Documented in the ELMCIP Electronic Literature Knowledge …
S Rettberg – ELO 2013 Conference paper. August, 2013 – elmcip.net
Page 1. An Emerging Canon? A Preliminary Analysis of All References to Creative Works in Critical Writing Documented in the ELMCIP Electronic Literature Knowledge Base (ELO 2013 Conference paper, August 2013 Draft) …

Unnatural Selection: Seeing Human Intelligence in Artificial Creations
T Veale – Journal of Artificial General Intelligence, 2015 – degruyter.com
… technique. As such, the mechanical aspects of the cut-up, which operate best when they operate without any regard to the meaning of the texts that are sliced and spliced, are easily implemented in a generative text system …

Interpretation of User Comments for Detection of Malicious Websites
M Sharifi – 2012 – lti.cs.cmu.edu
… Our approach removes the biases in traditional blacklist approach. • A natural language processing framework which maps text to a set of task-related concepts … information. Initial generative text models were based on n-grams, which consisted of counting the …

Digital Literature: Theoretical and Aesthetic Reflections
L GATTASS – 2011 – academia.edu
… (SIMANOWSKI, 2011; MANOVICH, 2001; STRINGER, 2001; KOSKIMAA, 2010). For illustration purposes, I scour concrete examples of generative text (the “textual instruments,” Regime Change (2003) and News Reader (2004) by Noah …

A Machine Learning Approach for Data Unification and Its Application in Asset Performance Management
B He – 2016 – vtechworks.lib.vt.edu
… understanding of the language. Natural language processing technology is still not Page 12. 4 … different stages of our data unification process. The most commonly used and well performing generative text classifier are Naïve Bayes classifiers [13] [17] …

The aesthetics of generative literature: lessons from a digital writing workshop
DC Howe, AB Soderman – Hyperrhiz: New Media Cultures, 2009 – hyperrhiz.io
… Other potentially viable areas include general language education (English, ESL, etc.), natural language generation tasks, and even computer-augmented literary … The question often arose concerning the best use of a writer’s time when working with generative text; on the …

The making of knowledge-makers in composition: A distant reading of dissertations
B Miller – 2015 – search.proquest.com
The making of knowledge-makers in composition: A distant reading of dissertations. Abstract. Combining qualitative coding with original algorithmic and quantitative analyses, this project aggregates and visualizes metadata …

Machine learning: discriminative and generative
T Jebara – 2012 – books.google.com
Page 1. | | !” USE iminative and Generatile . “. Springer Science+Business Media, LLC Page 2. |MACHINE LEARNING Discriminative and Generative Page 3. THE KLUWER INTERNATIONAL SERIES IN ENGINEERING AND COMPUTER SCIENCE Page 4 …

Datasets, features, learning, and models in visual recognition
G Wang – 2010 – search.proquest.com
… 5. One approach simply ignores spatial relationships between local features (thus it is called bag of features similar to the term bag of words popularly used in natural language processing and information … We adopt a generative text model and a discriminative image model …

Changeful Tales: Design-Driven Approaches Toward More Expressive Storygames
AA Reed – 2017 – search.proquest.com
Changeful Tales: Design-Driven Approaches Toward More Expressive Storygames. Abstract. Stories in released games are still based largely on static and predetermined structures, despite decades of academic work to make them more dynamic …

Three Papers in Political Methodology
BM Stewart – 2015 – search.proquest.com
… 6561934.htm. 23. Chapter 2. A model of text for experimentation in the social sciences. Allocaiton (LDA), the Dirichlet Multinomial Regression topic model (DMR), and the Sparse Additive Generative text model (SAGE). We use …

(Visited 34 times, 1 visits today)