| Year |
Citation |
Score |
| 2016 |
Beltagy I, Roller S, Cheng P, Erk K, Mooney RJ. Representing meaning with a combination of logical and distributional models Computational Linguistics. 42: 763-808. DOI: 10.1162/Coli_A_00266 |
0.426 |
|
| 2014 |
Acharya A, Mooney RJ, Ghosh J. Active multitask learning using both latent and supervised shared topics Siam International Conference On Data Mining 2014, Sdm 2014. 1: 190-198. DOI: 10.1137/1.9781611973440.22 |
0.365 |
|
| 2013 |
Raghavan S, Mooney RJ. Online inference-rule learning from natural-language extractions Aaai Workshop - Technical Report. 57-63. |
0.478 |
|
| 2013 |
Kim J, Mooney RJ. Adapting discriminative reranking to grounded language learning Acl 2013 - 51st Annual Meeting of the Association For Computational Linguistics, Proceedings of the Conference. 1: 218-227. |
0.355 |
|
| 2012 |
Mooney RJ. Machine Learning The Oxford Handbook of Computational Linguistics. DOI: 10.1093/oxfordhb/9780199276349.013.0020 |
0.421 |
|
| 2012 |
Kim J, Mooney RJ. Unsupervised PCFG induction for grounded language learning with highly ambiguous supervision Emnlp-Conll 2012 - 2012 Joint Conference On Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference. 433-444. |
0.323 |
|
| 2011 |
Huynh TN, Mooney RJ. Online structure learning for Markov logic networks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6912: 81-96. DOI: 10.1007/978-3-642-23783-6_6 |
0.326 |
|
| 2011 |
Mooney RJ. Learning language from its perceptual context Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6539: 2-4. DOI: 10.1007/978-3-642-18378-2_2 |
0.375 |
|
| 2011 |
Chen DL, Mooney RJ. Learning to interpret natural language navigation instructions from observations Proceedings of the National Conference On Artificial Intelligence. 1: 859-865. |
0.373 |
|
| 2010 |
Chen DL, Kim J, Mooney RJ. Training a multilingual sportscaster: Using perceptual context to learn language Journal of Artificial Intelligence Research. 37: 397-435. DOI: 10.1613/Jair.2962 |
0.476 |
|
| 2010 |
Kate RJ, Luo X, Patwardhan S, Franz M, Florian R, Mooney RJ, Roukos S, Welty C. Learning to predict readability using diverse linguistic features Coling 2010 - 23rd International Conference On Computational Linguistics, Proceedings of the Conference. 2: 546-554. |
0.748 |
|
| 2010 |
Kim J, Mooney RJ. Generative alignment and semantic parsing for learning from ambiguous supervision Coling 2010 - 23rd International Conference On Computational Linguistics, Proceedings of the Conference. 2: 543-551. |
0.39 |
|
| 2010 |
Kate RJ, Mooney RJ. Joint entity and relation extraction using card-pyramid parsing Conll 2010 - Fourteenth Conference On Computational Natural Language Learning, Proceedings of the Conference. 203-212. |
0.702 |
|
| 2009 |
Kulis B, Basu S, Dhillon I, Mooney R. Semi-supervised graph clustering: a kernel approach Machine Learning. 74: 1-22. DOI: 10.1007/S10994-008-5084-4 |
0.551 |
|
| 2009 |
Huynh TN, Mooney RJ. Max-margin weight learning for markov logic networks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5781: 564-579. DOI: 10.1007/978-3-642-04180-8_54 |
0.313 |
|
| 2008 |
Mooney RJ. Transfer learning by mapping and revising relational knowledge Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5249: 2-3. DOI: 10.1007/978-3-540-88190-2-2 |
0.335 |
|
| 2008 |
Huynh TN, Mooney RJ. Discriminative structure and parameter learning for Markov logic networks Proceedings of the 25th International Conference On Machine Learning. 416-423. |
0.34 |
|
| 2008 |
Mooney RJ. Learning to connect language and perception Proceedings of the National Conference On Artificial Intelligence. 3: 1598-1601. |
0.338 |
|
| 2008 |
Chen DL, Mooney RJ. Learning to sportscast: A test of grounded language acquisition Proceedings of the 25th International Conference On Machine Learning. 128-135. |
0.326 |
|
| 2007 |
Bunescu RC, Mooney RJ. Multiple instance learning for sparse positive bags Acm International Conference Proceeding Series. 227: 105-112. DOI: 10.1145/1273496.1273510 |
0.715 |
|
| 2007 |
Bunescu RC, Mooney RJ. Extracting relations from text: From word sequences to dependency paths Natural Language Processing and Text Mining. 29-44. DOI: 10.1007/978-1-84628-754-1_3 |
0.739 |
|
| 2007 |
Kate RJ, Mooney RJ. Learning language semantics from ambiguous supervision Proceedings of the National Conference On Artificial Intelligence. 1: 895-900. |
0.772 |
|
| 2007 |
Wong YW, Mooney RJ. Learning synchronous grammars for semantic parsing with lambda calculus Acl 2007 - Proceedings of the 45th Annual Meeting of the Association For Computational Linguistics. 960-967. |
0.401 |
|
| 2007 |
Wong YW, Mooney RJ. Generation by inverting a semantic parser that uses statistical machine translation Naacl Hlt 2007 - Human Language Technologies 2007: the Conference of the North American Chapter of the Association For Computational Linguistics, Proceedings of the Main Conference. 172-179. |
0.329 |
|
| 2007 |
Mooney RJ. Learning for semantic parsing Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4394: 311-324. |
0.356 |
|
| 2007 |
Bunescu RC, Mooney RJ. Learning to extract relations from the web using minimal supervision Acl 2007 - Proceedings of the 45th Annual Meeting of the Association For Computational Linguistics. 576-583. |
0.75 |
|
| 2006 |
Wong YW, Mooney RJ. Learning for semantic parsing with statistical machine translation Hlt-Naacl 2006 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings of the Main Conference. 439-446. |
0.392 |
|
| 2006 |
Kate RJ, Mooney RJ. Using string-kernels for learning semantic parsers Coling/Acl 2006 - 21st International Conference On Computational Linguistics and 44th Annual Meeting of the Association For Computational Linguistics, Proceedings of the Conference. 1: 913-920. |
0.758 |
|
| 2005 |
Ramani AK, Bunescu RC, Mooney RJ, Marcotte EM. Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome. Genome Biology. 6: R40. PMID 15892868 DOI: 10.1186/Gb-2005-6-5-R40 |
0.686 |
|
| 2005 |
Bunescu R, Ge R, Kate RJ, Marcotte EM, Mooney RJ, Ramani AK, Wong YW. Comparative experiments on learning information extractors for proteins and their interactions. Artificial Intelligence in Medicine. 33: 139-55. PMID 15811782 DOI: 10.1016/J.Artmed.2004.07.016 |
0.79 |
|
| 2005 |
Mooney RJ, Bunescu R. Mining knowledge from text using information extraction Acm Sigkdd Explorations Newsletter. 7: 3-10. DOI: 10.1145/1089815.1089817 |
0.764 |
|
| 2005 |
Melville P, Mooney RJ. Creating diversity in ensembles using artificial data Information Fusion. 6: 99-111. DOI: 10.1016/J.Inffus.2004.04.001 |
0.756 |
|
| 2005 |
Melville P, Yang SM, Saar-Tsechansky M, Mooney R. Active learning for probability estimation using jensen-shannon divergence Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3720: 268-279. DOI: 10.1007/11564096_28 |
0.304 |
|
| 2005 |
Bunescu RC, Mooney RJ. Subsequence kernels for relation extraction Advances in Neural Information Processing Systems. 171-178. |
0.741 |
|
| 2005 |
Ge R, Mooney RJ. A Statistical semantic parser that integrates syntax and semantics Conll 2005 - Proceedings of the Ninth Conference On Computational Natural Language Learning. 9-16. |
0.309 |
|
| 2005 |
Kate RJ, Wong YW, Mooney RJ. Learning to transform natural to formal languages Proceedings of the National Conference On Artificial Intelligence. 3: 1062-1068. |
0.737 |
|
| 2005 |
Bunescu RC, Mooney RJ. A shortest path dependency kernel for relation extraction Hlt/Emnlp 2005 - Human Language Technology Conference and Conference On Empirical Methods in Natural Language Processing, Proceedings of the Conference. 724-731. |
0.731 |
|
| 2004 |
Califf ME, Mooney RJ. Bottom-up relational learning of pattern matching rules for information extraction Journal of Machine Learning Research. 4: 177-210. DOI: 10.1162/153244304322972685 |
0.527 |
|
| 2004 |
Nahm UY, Mooney RJ. Using soft-matching mined rules to improve information extraction Aaai Workshop - Technical Report. 27-32. |
0.772 |
|
| 2004 |
Melville P, Mooney RJ. Diverse ensembles for active learning Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 584-591. |
0.327 |
|
| 2004 |
Mooney RJ. Learning semantic parsers: An important but under-studied problem Aaai Spring Symposium - Technical Report. 5: 39-44. |
0.354 |
|
| 2003 |
Thompson CA, Mooney RJ. Acquiring word-meaning mappings for natural language interfaces Journal of Artificial Intelligence Research. 18: 1-44. DOI: 10.1613/Jair.1063 |
0.518 |
|
| 2003 |
Bilenko M, Mooney R, Cohen W, Ravikumar P, Fienberg S. Adaptive name matching in information integration Ieee Intelligent Systems. 18: 16-23. DOI: 10.1109/Mis.2003.1234765 |
0.726 |
|
| 2003 |
Melville P, Mooney RJ. Constructing diverse classifier ensembles using artificial training examples Ijcai International Joint Conference On Artificial Intelligence. 505-510. |
0.354 |
|
| 2002 |
Nahm UY, Mooney RJ. Mining soft-matching association rules International Conference On Information and Knowledge Management, Proceedings. 681-683. |
0.735 |
|
| 2001 |
Tang LR, Mooney RJ. Using multiple clause constructors in inductive logic programming for semantic parsing Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2167: 466-477. |
0.356 |
|
| 2001 |
Nahm UY, Mooney RJ. Mining soft-matching rules from textual data Ijcai International Joint Conference On Artificial Intelligence. 979-984. |
0.785 |
|
| 2001 |
Basu S, Mooney RJ, Pasupuleti KV, Ghosh J. Evaluating the novelty of text-mined rules using lexical knowledge Proceedings of the Seventh Acm Sigkdd International Conference On Knowledge Discovery and Data Mining. 233-238. |
0.318 |
|
| 2000 |
Mooney RJ. Learning for semantic interpretation: Scaling up without dumbing down Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1925: 57-66. |
0.372 |
|
| 1999 |
Cardie C, Mooney RJ. Guest Editors‘ Introduction: Machine Learning and Natural Language Machine Learning. 34: 5-9. DOI: 10.1023/A:1007580931600 |
0.409 |
|
| 1998 |
Califf ME, Mooney RJ. Advantages of decision lists and implicit negatives in inductive logic programming New Generation Computing. 16: 263-281. DOI: 10.1007/Bf03037482 |
0.359 |
|
| 1997 |
Brill E, Mooney RJ. An Overview of Empirical Natural Language Processing Ai Magazine. 18: 13-24. DOI: 10.1609/Aimag.V18I4.1318 |
0.462 |
|
| 1997 |
Mooney RJ. Inductive logic programming for natural language processing Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1314: 3-22. |
0.34 |
|
| 1995 |
Mooney RJ, Califf ME. Induction of first-order decision lists: results on learning the past tense of English verbs Journal of Artificial Intelligence Research. 3: 1-24. DOI: 10.1613/Jair.148 |
0.459 |
|
| 1995 |
Mooney RJ. Encouraging Experimental Results on Learning CNF Machine Learning. 19: 79-92. DOI: 10.1023/A:1022659107719 |
0.459 |
|
| 1995 |
Richards BL, Mooney RJ. Automated Refinement of First-Order Horn-Clause Domain Theories Machine Learning. 19: 95-131. DOI: 10.1023/A:1022611224557 |
0.329 |
|
| 1994 |
Mooney RJ, Zelle JM. Integrating ILP and EBL Intelligence\/Sigart Bulletin. 5: 12-21. DOI: 10.1145/181668.181673 |
0.426 |
|
| 1994 |
Ourston D, Mooney RJ. Theory refinement combining analytical and empirical methods Artificial Intelligence. 66: 273-309. DOI: 10.1016/0004-3702(94)90028-0 |
0.366 |
|
| 1993 |
Mahoney JJ, Mooney RJ. Combining Connectionist and Symbolic Learning to Refine Certainty Factor Rule Bases Connection Science. 5: 339-364. DOI: 10.1080/09540099308915704 |
0.488 |
|
| 1993 |
Mooney RJ. Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning Machine Learning. 10: 79-110. DOI: 10.1023/A:1022616711064 |
0.416 |
|
| 1993 |
Mooney RJ. Integrating Theory and Data in Category Learning Psychology of Learning and Motivation - Advances in Research and Theory. 29: 189-218. DOI: 10.1016/S0079-7421(08)60140-1 |
0.394 |
|
| 1992 |
Ahn Wk, Brewer WF, Mooney RJ. Schema Acquisition From a Single Example Journal of Experimental Psychology: Learning, Memory, and Cognition. 18: 391-412. DOI: 10.1037/0278-7393.18.2.391 |
0.443 |
|
| 1991 |
Shavlik JW, Mooney RJ, Towell GG. Symbolic and Neural Learning Algorithms: An Experimental Comparison Machine Learning. 6: 111-143. DOI: 10.1023/A:1022602303196 |
0.691 |
|
| 1990 |
Mooney RJ. Learning plan schemata from observation: Explanation-based learning for plan recognition Cognitive Science. 14: 483-509. DOI: 10.1016/0364-0213(90)90007-J |
0.423 |
|
| 1986 |
Dejong G, Mooney R. Explanation-Based Learning: An Alternative View Machine Learning. 1: 145-176. DOI: 10.1023/A:1022898111663 |
0.763 |
|
| Show low-probability matches. |