Natural Language Processing
Natural Language Processing is a broad area that includes various approaches to building computational systems that understand and generate language, as well as categorization and analysis of text documents, and cognitive models of human language processing.
Subareas:
People
     [Expand to show all 15][Minimize]
I. Beltagy Ph.D. Alumni beltagy [at] cs utexas edu
Yinon Bentor Formerly affiliated Ph.D. Student yinon [at] cs utexas edu
Rodolfo Corona Undergraduate Alumni rud721 [at] gmail com
James Jumin Fan Ph.D. Alumni jfan [at] cs utexas edu
Dan Garrette Ph.D. Alumni dhg [at] cs utexas edu
Angela S. Lin Masters Alumni alin [at] cs utexas edu
Angela S. Lin Masters Alumni alin [at] cs utexas edu
Raymond J. Mooney Faculty mooney [at] cs utexas edu
Aishwarya Padmakumar Ph.D. Alumni aish [at] cs utexas edu
Sheena Panthaplackel Ph.D. Alumni spantha [at] cs utexas edu
Nazneen Rajani Ph.D. Alumni nrajani [at] cs utexas edu
Stephen Roller Ph.D. Alumni roller [at] cs utexas edu
Julia Strout Masters Alumni jstrout [at] utexas edu
Jesse Thomason Ph.D. Alumni thomason DOT jesse AT gmail
Subhashini Venugopalan Ph.D. Alumni vsub [at] cs utexas edu
Publications
     [Expand to show all 112][Minimize]
Sparse Meets Dense: A Hybrid Approach to Enhance Scientific Document Retrieval 2024
Priyanka Mandikal, Raymond Mooney, The 4th Workshop on Scientific Document Understanding, AAAI (2024).
“Female Astronaut: Because sandwiches won’t make themselves up there!": Towards multi-modal misogyny detection in memes 2023
Smriti Singh, Amritha Haridasan, Raymond Mooney, Association of Computational Linguistics (ACL), Workshop on Online Abuse and Harms (WOAH) (2023).
Updated Headline Generation: Creating Updated Summaries for Evolving News Stories 2022
Sheena Panthaplackel, Adrian Benton, Mark Dredze, In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, May 2022.
Using Commonsense Knowledge to Answer Why-Questions 2022
Yash Kumar Lal, Niket Tandon, Tanvi Aggarwal, Horace Liu, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian, In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, December 2022.
Facilitating Software Evolution through Natural Language Comments and Dialogue 2021
Sheena Panthaplackel, Ph.D. Proposal.
TellMeWhy: A Dataset for Answering Why-Questions in Narratives 2021
Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian, In Findings of ACL 2021, August 2021.
Using Natural Language to Aid Task Specification in Sequential Decision Making Problems 2021
Prasoon Goyal, Ph.D. Proposal.
Dialog as a Vehicle for Lifelong Learning 2020
Aishwarya Padmakumar, Raymond J. Mooney, In Position Paper Track at the SIGDIAL Special Session on Physically Situated Dialogue (RoboDial 2.0), July 2020.
Evaluating the Robustness of Natural Language Reward Shaping Models to Spatial Relations 2020
Antony Yun, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Using Natural Language for Reward Shaping in Reinforcement Learning 2019
Prasoon Goyal, Scott Niekum, Raymond J. Mooney, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, Macao, China, August 2019.
Explainable Improved Ensembling for Natural Language and Vision 2018
Nazneen Rajani, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Advances in Statistical Script Learning 2017
Karl Pichotta, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Captioning Images with Diverse Objects 2017
Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond Mooney, Trevor Darrell, and Kate Saenko, In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR-17), pp. 5753--5761 2017.
Dialog for Language to Code 2017
Shobhit Chaurasia and Raymond J. Mooney, In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 175-180, Taipei, Taiwan, November 2017.
Dialog for Natural Language to Code 2017
Shobhit Chaurasia, Masters Thesis, Computer Science Department, University of Texas at Austin.
Distributional modeling on a diet: One-shot word learning from text only 2017
Su Wang, Stephen Roller, and Katrin Erk, In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), Taipei, Taiwan, November 2017.
Guiding Interaction Behaviors for Multi-modal Grounded Language Learning 2017
Jesse Thomason, Jivko Sinapov, and Raymond J. Mooney, In Proceedings of the Workshop on Language Grounding for Robotics at ACL 2017 (RoboNLP-17), Vancouver, Canada, August 2017.
Integrated Learning of Dialog Strategies and Semantic Parsing 2017
Aishwarya Padmakumar, Jesse Thomason, and Raymond J. Mooney, In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2017), pp. 547--557, Valencia, Spain, April 2017.
Leveraging Discourse Information Effectively for Authorship Attribution 2017
Elisa Ferracane, Su Wang, and Raymond J. Mooney, In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 584–593, Taipei, Taiwan, November 2017.
Multi-Modal Word Synset Induction 2017
Jesse Thomason and Raymond J. Mooney, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 4116--4122, Melbourne, Australia 2017.
Natural-Language Video Description with Deep Recurrent Neural Networks 2017
Subhashini Venugopalan, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Stacking With Auxiliary Features 2017
Nazneen Fatema Rajani and Raymond J. Mooney, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 2634-2640, Melbourne, Australia 2017.
An Analysis of Using Semantic Parsing for Speech Recognition 2016
Rodolfo Corona, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Combining Supervised and Unsupervised Ensembles for Knowledge Base Population 2016
Nazneen Fatema Rajani and Raymond J. Mooney, To Appear In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16) 2016.
Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception 2016
Jesse Thomason, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data 2016
Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond Mooney, Kate Saenko, and Trevor Darrell, In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR-16), pp. 1--10 2016.
Improved Semantic Parsers For If-Then Statements 2016
I. Beltagy and Chris Quirk, To Appear In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), Berlin, Germany 2016.
Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text 2016
Subhashini Venugopalan, Lisa Anne Hendricks, Raymond Mooney, and Kate Saenko, In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), pp. 1961--1966, Austin, Texas 2016.
Learning Statistical Scripts with LSTM Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, February 2016.
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification 2016
Ye Zhang, Stephen Roller, and Byron Wallace., In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1522--1527, San Diego, California 2016.
Natural Language Semantics Using Probabilistic Logic 2016
I. Beltagy, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
PIC a Different Word: A Simple Model for Lexical Substitution in Context 2016
Stephen Roller and Katrin Erk, In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1121-1126, San Diego, California 2016.
Representing Meaning with a Combination of Logical and Distributional Models 2016
I. Beltagy, Stephen Roller, Pengxiang Cheng, Katrin Erk, and Raymond J. Mooney, The special issue of Computational Linguistics on Formal Distributional Semantics, Vol. 42, 4 (2016).
Stacking With Auxiliary Features for Combining Supervised and Unsupervised Ensembles 2016
Nazneen Fatema Rajani and Raymond J. Mooney, In Proceedings of the Ninth Text Analysis Conference (TAC 2016) 2016.
Stacking With Auxiliary Features: Improved Ensembling for Natural Language and Vision 2016
Nazneen Fatema Rajani, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Statistical Script Learning with Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the Workshop on Uphill Battles in Language Processing (UBLP) at EMNLP 2016, Austin, TX, November 2016.
Using Sentence-Level LSTM Language Models for Script Inference 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), pp. 279--289, Berlin, Germany 2016.
A Supertag-Context Model for Weakly-Supervised CCG Parser Learning 2015
Dan Garrette, Chris Dyer, Jason Baldridge, and Noah A. Smith , In Proceedings of the 2015 Conference on Computational Natural Language Learning (CoNLL-2015), pp. 22--31, Beijing, China 2015.
Inducing Grammars from Linguistic Universals and Realistic Amounts of Supervision 2015
Dan Garrette, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Knowledge Base Population using Stacked Ensembles of Information Extractors 2015
Vidhoon Viswanathan, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes 2015
Chris Quirk, Raymond Mooney, and Michel Galley, In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), pp. 878--888, Beijing, China, July 2015.
Natural Language Video Description using Deep Recurrent Neural Networks 2015
Subhashini Venugopalan, PhD proposal, Department of Computer Science, The University of Texas at Austin.
On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics 2015
I. Beltagy and Katrin Erk, In Proceedings of the 11th International Conference on Computational Semantics (IWCS-2015), London, UK, April 2015.
Sequence to Sequence -- Video to Text 2015
Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond J. Mooney, Trevor Darrell, and Kate Saenko, In Proceedings of the 2015 International Conference on Computer Vision (ICCV-15), Santiago, Chile, December 2015.
Stacked Ensembles of Information Extractors for Knowledge-Base Population 2015
Vidhoon Viswanathan, Nazneen Fatema Rajani, Yinon Bentor, and Raymond J. Mooney, In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), pp. 177-187, Beijing, China, July 2015.
Stacked Ensembles of Information Extractors for Knowledge-Base Population by Combining Supervised and Unsupervised Approaches 2015
Nazneen Fatema Rajani and Raymond J Mooney, In Proceedings of the Eighth Text Analysis Conference (TAC 2015), November 2015.
Statistical Script Learning with Recurrent Neural Nets 2015
Karl Pichotta, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Translating Videos to Natural Language Using Deep Recurrent Neural Networks 2015
Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, and Kate Saenko, In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), pp. 1494--1504, Denver, Colora...
Unsupervised Code-Switching for Multilingual Historical Document Transcription 2015
Dan Garrette, Hannah Alpert-Abrams, Taylor Berg-Kirkpatrick, and Dan Klein , In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), pp. 1036--1041, Denver, Colora...
Weakly-Supervised Grammar-Informed Bayesian CCG Parser Learning 2015
Dan Garrette, Chris Dyer, Jason Baldridge, Noah A. Smith, In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, TX, January 2015.
Efficient Markov Logic Inference for Natural Language Semantics 2014
I. Beltagy and Raymond J. Mooney, In Proceedings of the Fourth International Workshop on Statistical Relational AI at AAAI (StarAI-2014), pp. 9--14, Quebec City, Canada, July 2014.
Inclusive yet Selective: Supervised Distributional Hypernymy Detection 2014
Stephen Roller, Katrin Erk, and Gemma Boleda, In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), pp. 1025--1036, Dublin, Ireland, August 2014.
Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild 2014
Jesse Thomason, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, and Raymond Mooney, In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), pp. 1218--1227, Dublin, Ireland, August 2014.
Integrating Visual and Linguistic Information to Describe Properties of Objects 2014
Calvin MacKenzie, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Natural Language Semantics using Probabilistic Logic 2014
I. Beltagy, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Probabilistic Soft Logic for Semantic Textual Similarity 2014
I. Beltagy, Katrin Erk, and Raymond J. Mooney, In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-14), pp. 1210--1219, Baltimore, MD 2014.
Semantic Parsing using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Katrin Erk, and Raymond Mooney, In Proceedings of ACL 2014 Workshop on Semantic Parsing (SP-2014), pp. 7--11, Baltimore, MD, June 2014.
Statistical Script Learning with Multi-Argument Events 2014
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2014), pp. 220--229, Gothenburg, Sweden, April 2014.
UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Stephen Roller, Gemma Boleda, and Katrin Erk, and Raymond J. Mooney, In The 8th Workshop on Semantic Evaluation (SemEval-2014), pp. 796--801, Dublin, Ireland, August 2014.
Weakly-Supervised Bayesian Learning of a CCG Supertagger 2014
Dan Garrette, Chris Dyer, Jason Baldridge, and Noah A. Smith, In Proceedings of the Eighteenth Conference on Computational Natural Language Learning (CoNLL-2014), pp. 141--150, Baltimore, MD, June 2014.
A Formal Approach to Linking Logical Form and Vector-Space Lexical Semantics 2013
Dan Garrette, Katrin Erk, Raymond J. Mooney, In Computing Meaning, Harry Bunt, Johan Bos, and Stephen Pulman (Eds.), Vol. 4, pp. 27--48, Berlin 2013. Springer.
A Multimodal LDA Model Integrating Textual, Cognitive and Visual Modalities 2013
Stephen Roller and Sabine Schulte im Walde, In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 1146--1157, Seattle, WA, October 2013.
Adapting Discriminative Reranking to Grounded Language Learning 2013
Joohyun Kim and Raymond J. Mooney, In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013), pp. 218--227, Sofia, Bulgaria, August 2013.
Detecting Promotional Content in Wikipedia 2013
Shruti Bhosale, Heath Vinicombe, and Raymond J. Mooney, In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 1851--1857, Seattle, WA, October 2013.
Generating Natural-Language Video Descriptions Using Text-Mined Knowledge 2013
Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J. Mooney, Kate Saenko, Sergio Guadarrama, In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI-2013), pp. 541--547, July 2013.
Grounded Language Learning Models for Ambiguous Supervision 2013
Joo Hyun Kim, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Identifying Phrasal Verbs Using Many Bilingual Corpora 2013
Karl Pichotta and John DeNero, In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 636--646, Seattle, WA, October 2013.
Learning a Part-of-Speech Tagger from Two Hours of Annotation 2013
Dan Garrette, Jason Baldridge , Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT-13) (2013), pp. 138--147.
Logic Programs vs. First-Order Formulas in Textual Inference 2013
Yuliya Lierler and Vladimir Lifschitz, 10th International Conference on Computational Semantics (IWCS) (2013).
Montague Meets Markov: Deep Semantics with Probabilistic Logical Form 2013
I. Beltagy, Cuong Chau, Gemma Boleda, Dan Garrette, Katrin Erk, Raymond Mooney, Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*Sem-2013) (2013), pp. 11--21.
Online Inference-Rule Learning from Natural-Language Extractions 2013
Sindhu Raghavan and Raymond J. Mooney, In Proceedings of the 3rd Statistical Relational AI (StaRAI-13) workshop at AAAI '13, July 2013.
Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages 2013
Dan Garrette, Jason Mielens, and Jason Baldridge , Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013) (2013), pp. 583--592.
Role of KR in Natural Language Understanding and Synergic KR 2013
Yuliya Lierler, NSF Workshop: Research Challenges and Opportunities in Knowledge Representation (2013).
Towards a Tight Integration of Syntactic Parsing with Semantic Disambiguation by means of Declarative Programming 2013
Yuliya Lierler and Peter Schueller, 10th International Conference on Computational Semantics (IWCS) (2013).
University of Texas at Austin KBP 2013 Slot Filling System: Bayesian Logic Programs for Textual Inference 2013
Yinon Bentor, Amelia Harrison, Shruti Bhosale, and Raymond Mooney, In Proceedings of the Sixth Text Analysis Conference (TAC 2013) 2013.
YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-shot Recognition 2013
Sergio Guadarrama, Niveda Krishnamoorthy, Girish Malkarnenkar, Subhashini Venugopalan, Raymond Mooney, Trevor Darrell, Kate Saenko, In Proceedings of the 14th International Conference on Computer Vision (ICCV-2013), pp. 2712--2719, Sydney, Australia, December 2013.
Bayesian Logic Programs for Plan Recognition and Machine Reading 2012
Sindhu Raghavan, PhD Thesis, Department of Computer Science, University of Texas at Austin. 170.
Fast Online Lexicon Learning for Grounded Language Acquisition 2012
David L. Chen, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL-2012) (2012), pp. 430--439.
Generative Models of Grounded Language Learning with Ambiguous Supervision 2012
Joohyun Kim, Technical Report, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Improving Video Activity Recognition using Object Recognition and Text Mining 2012
Tanvi S. Motwani and Raymond J. Mooney, In Proceedings of the 20th European Conference on Artificial Intelligence (ECAI-2012), pp. 600--605, August 2012.
Latent Variable Models of Distributional Lexical Semantics 2012
Joseph Reisinger, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Learning Language from Ambiguous Perceptual Context 2012
David L. Chen, PhD Thesis, Department of Computer Science, University of Texas at Austin. 196.
Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries 2012
Dan Garrette and Jason Baldridge, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012), pp. 821--831, Jeju, Korea, July 2012.
Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision 2012
Joohyun Kim and Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning (EMNLP-CoNLL '12), pp. 433--444, Jeju Island, Korea, July 2012.
Building a Persistent Workforce on Mechanical Turk for Multilingual Data Collection 2011
David L. Chen and William B. Dolan, In Proceedings of The 3rd Human Computation Workshop (HCOMP 2011), August 2011.
Collecting Highly Parallel Data for Paraphrase Evaluation 2011
David L. Chen and William B. Dolan, In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pp. 190-200, Portland, Oregon, USA, June 2011.
Fine-Grained Class Label Markup of Search Queries 2011
Joseph Reisinger and Marius Pasca, In Proceedings of The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), pp. 1200-1209, June 2011.
Integrating Logical Representations with Probabilistic Information using Markov Logic 2011
Dan Garrette, Katrin Erk, Raymond Mooney, In Proceedings of the International Conference on Computational Semantics, pp. 105--114, Oxford, England, January 2011.
Panning for Gold: Finding Relevant Semantic Content for Grounded Language Learning 2011
David L. Chen and Raymond J. Mooney, In Proceedings of Symposium on Machine Learning in Speech and Language Processing (MLSLP 2011), June 2011.
Authorship Attribution Using Probabilistic Context-Free Grammars 2010
Sindhu Raghavan, Adriana Kovashka and Raymond Mooney, In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL-2010), pp. 38--42 2010.
Learning to Predict Readability using Diverse Linguistic Features 2010
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan, Martin Franz, Radu Florian, Raymond J. Mooney, Salim Roukos and Chris Welty, In 23rd International Conference on Computational Linguistics (COLING 2010) 2010.
Knowledge integration across multiple texts 2009
Doo Soon Kim, Ken Barker, and Bruce Porter, In The Fifth International Conference on Knowledge Capture (KCAP2009) 2009.
Constructing a semantic interpreter using distributional analysis 2009
Michael Glass, Ken Barker, Rekha Kumar, Guhan Ravi and Bruce Porter, In Proceedings of the Eighth Conference of the Pacific Association for Computational Linguistics 2009.
Kleo: A Bootstrapping Learning-by-reading System 2009
Doo Soon Kim and Bruce Porter, In AAAI Spring Symposium on Learning by Reading and Learning to Read 2009.
Improving semantic integration by learning semantic interpretation rules 2008
Michael Glass and Bruce Porter, In AAAI Spring Symposium on Semantic Scientific Knowledge Integration 2008.
Knowledge Representation and Question Answering 2008
Marcello Balduccini, Chitta Baral, Yuliya Lierler, In Handbook of Knowledge Representation, Frank van Harmelen and Vladimir Lifschitz and Bruce Porter (Eds.), pp. 779-820 2008. Elsevier.
Following Natural Language Route Instructions 2007
Matthew T. MacMahon, PhD Thesis, Electrical and Computer Engineering Department, University of Texas at Austin.
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned 2007
Ken Barker, Bhalchandra Agashe, Shaw-Yi Chaw, James Fan, Noah Friedland, Michael Glass, Jerry Hobbs, Eduard Hovy, David Israel, Doo Soon Kim, Rutu Mulkar-Mehta, Sourabh Patwardhan, Bruce Porter, Dan Tecuci, and Peter Yeh, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI 2007) 2007.
Indirect Anaphora Resolution as Semantic Path Search 2005
James Fan, Ken Barker, Bruce Porter, In Proceedings of Third International Conference on Knowledge Capture 2005.
Interpreting Loosely Encoded Questions 2004
James Fan, Bruce Porter, In Proceedings of the Nineteenth National Conference on Artificial Intelligence 2004.
Associative Anaphora Resolution: A Web-Based Approach 2003
Razvan Bunescu, In Proceedings of the EACL-2003 Workshop on the Computational Treatment of Anaphora, pp. 47-52, Budapest, Hungary 2003.
Machine Learning 2003
Raymond J. Mooney, , McGraw-Hill, New York, NY 2003. McGraw-Hill.
The Knowledge Required to Interpret Noun Compounds 2003
James Fan, Ken Barker, Bruce Porter, In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence 2003.
Learning Parse and Translation Decisions From Examples With Rich Context 1997
Ulf Hermjakob, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 175 pages. Technical Report UT-AI97-261.
Learning Parse and Translation Decisions From Examples With Rich Context 1997
Ulf Hermjakob and Raymond J. Mooney, In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL'97/EACL'97), pp. 482-489, July 1997.
Comparative Results on Using Inductive Logic Programming for Corpus-based Parser Construction 1996
John M. Zelle and Raymond J. Mooney, In Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, Stefan Wermter and Ellen Riloff and Gabriela Scheler (Eds.), pp. 355-369, Berlin 1996. Spri...
Learning the Past Tense of English Verbs Using Inductive Logic Programming 1996
Raymond J. Mooney and Mary Elaine Califf, In Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, {S. Wermter, E. Riloff} and G. Scheler (Eds.), pp. 370-384, Berlin 1996. Springer.
Robust Natural Language Generation from Large-Scale Knowledge Bases 1995
Charles B. Callaway and James Lester, In Proceedings of the Fourth Bar-Ilan Symposium on the Foundations of AI 1995.
A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding 1988
Raymond J. Mooney, Ph.D. thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1988
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, In Proceedings of the Third International Machine Learning Workshop, pp. 126--128, New Brunswick, New Jersey 1985.
Learning Schemata for Natural Language Processing 1985
Raymond J. Mooney and Gerald F. DeJong, In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85), pp. 681-687, Los Angeles, CA, August 1985.
Labs
Knowledge Representation & Reasoning Machine Learning