Knowledge-Intensive Artificial Intelligence (KIAI) discusses the research progress of our team. Currently, the meeting is intended to deeply discuss the current progress of each member rather than to study relevant previous work (still, observers are welcome!). In every meeting, all the members will talk about their research progress in 5 minutes. It is recommended that all the members bring a short note or slides to describe their progress for an active discussion. The schedule is listed below.
- Date
- 前期: Friday 16:00-17:30 後期: Friday 10:30-12:00 ひとり20分まで
- Member
- 乾，井之上，杉浦，山本，Daiqin，Paul，大野，小林，横井，島岡，高橋，佐藤
- Related Keywords
- 人工知能/Artificial Intelligence，物語理解/Story Understanding，プラン/Plan，修辞構造/Rhetorical Structure，照応/Anaphora，省略/Ellipsis，ゼロ照応/Zero Anaphora
Schedule †
- 3/18 (Fri) 10:30-
- 1分チーム
- 5分チーム
- 小林 内部資料
- 10分チーム
- 5分チーム
- 横井 内部資料 (issue-id 200) (キリ番get) (2000年前後のインターネット)
- 2/5 (Fri) 10:00-
- 1/15 (Fri) 10:30-
- 1/8 (Fri) 10:30-
- 12/25 (Fri) 10:30-
- 12/18 (Fri) 10:30-
- 12/11 (Fri) 10:30-
- 12/4 (Fri) 10:30-
- 8/13 (Thu) 15:00-
- 横井: 🔒内部資料
- 7/24 (Fri) 16:00-
- 井之上: 🔒内部資料
- ASP tutorial: http://www.cs.nmsu.edu/~tson/tutorials/asp-tutorial.pdf
- 山本: 🔒内部資料
- 杉浦: 🔒内部資料
- Martin: 🔒内部資料
- 井之上: 🔒内部資料
- 1/9 (Fri) 10:30-
- 12/19 (Fri) 10:30-
- 11/28 (Fri) 10:30-
- 11/21 (Fri) 11:00-
- 11/14 (Fri) 11:00-
- 11/7 (Fri) 11:00-
Daily analysis †
- 2/16 (Mon)
John fired Dave because he had too many absences.
- 2/17 (Tue)
The FDA revoked the medical licenses of corrupt doctors because they have been improperly issuing drugs. The lifeguards evacuated the swimmers from the public pool because they were in danger of getting sick from human wastes in the water. The employer offered Katie a job, because she liked the interviewee. ... 8 more
- 2/18 (Wed)
The Detroit Lions beat the Dallas Cowboys because they had more desire to win. The car beat the bike because it was faster. Sally gave Kelly a doll because she had extra dolls. ... 11 more
- 2/19 (Thu)
John disliked Bill and he did not pick him. Steve Urkel was always annoying Carl Winslow in the show, "Family Matters", but he still liked him regardless.
Links †
Artificial Intelligence †
- Levesque, Hector J. "On our best behaviour." The 23rd International Joint Conference on Artificial Intelligence (IJCAI). August. 2013. pdf
- Rahman, Altaf, and Vincent Ng. "Resolving complex cases of definite pronouns: the winograd schema challenge." Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Association for Computational Linguistics, 2012. pdf dataset dataset 2
- Roemmele, Melissa, Cosmin Adrian Bejan, and Andrew S. Gordon. "Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning." AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. 2011. pdf dataset
- Levesque, Hector J., Ernest Davis, and Leora Morgenstern. "The Winograd schema challenge." AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. 2011. pdf
- Jerry R. Hobbs, Mark Stickel, Douglas Appelt, and Paul Martin. Interpretation as Abduction, Artificial Intelligence, 1993. pdf
Logical Inference †
- Mohammad Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa Walker Orr, Prasad Tadepalli, and Xiaoli Fern. Inverting Grice’s Maxims to Learn Rules from Natural Language Extractions. NIPS 2011. pdf
- Ekaterina Ovchinnikova, Niloofar Montazeri, Theodore Alexandrov, Jerry R. Hobbs, Michael C. McCord and Rutu Mulkar-Mehta. Abductive Reasoning with a Large Knowledge Base for Discourse Processing. IWCS 2011. pdf
- James Blythe, Jerry R. Hobbs, Pedro Domingos, Rohit J. Kate and Raymond J. Mooney. Implementing Weighted Abduction in Markov Logic. IWCS2011. pdf
- Dan Garrette, Katrin Erk, Raymond Mooney. Integrating Logical Representations with Probabilistic Information using Markov Logic. IWCS2011. pdf
- Sindhu V. Raghavan, Raymond J. Mooney. Bayesian Abductive Logic Programs. AAAI 2010. pdf
- RohitJ. Kate RaymondJ. Mooney. Probabilistic Abduction using Markov Logic Networks. IJCAI 2009 on PAIR 2009. pdf
- Jerry R. Hobbs, Mark Stickel, Douglas Appelt, and Paul Martin. Interpretation as Abduction, Artificial Intelligence, 1993. pdf
- J. Bos (2009): Applying automated deduction to natural language understanding. Journal of Applied Logic 7(1): 100–112. pdf
- A Unified Approach to Abductive Inference (ARO 2008 MURI Project@University of Washington)
Discourse Theory †
- Rhetorical Structure Theory
- Discourse Representation Theory
- J. Bos, M. Nissim (2008): Combining Discourse Representation Theory with FrameNet. In: R. Rossini Favretti (ed): Frames, Corpora, and Knowledge Representation, pp 169–183, Bononia University Press. pdf
- Dan Cristea, Nancy Ide and Laurent Romary. Veins Theory: A Model of Global Discourse Cohesion and Coherence. ACL 1998. pdf
- Barbara J. Grosz, Aravind K. Joshi and Scott Weinstein. Centering: A Framework for Modeling the Local Coherence of Discourse. Computational Linguistics, 1995. pdf
- Barbara J. Grosz and Candace L. Sidner. ATTENTION, INTENTIONS, AND THE STRUCTURE OF DISCOURSE. Computational Linguistics, 1986. pdf
- Bonnie Webber. Accounting for Discourse Relations: Constituency and Dependency. Intelligent Linguistic Architectures, 2006. pdf
- Florian Wolf, Edward Gibson. Representing Discourse Coherence: A Corpus-Based Study. Computational Linguistics, 2005.
- Bonnie Webber, Matthew Stone, Aravind Joshi and Alistair Knott. Anaphora and Discourse Structure. Computational Linguistics, 2003. pdf
- Daniel Marcu. A Formal and Computational Synthesis of Grosz and Sidner's and Mann and Thompson's theories. 1999. pdf
- Erhard Hinrichs. Discourse Annotation of Corpora. pdf
- Johanna D. Moore and Martha E. Pollack. A Problem for RST: The Need for Multi-Level Discourse Analysis. Computational Linguistics, 1992. pdf
Discourse Parsing †
- Alexis Palmer, Afra Alishahi and Caroline Sporleder. Robust Semantic Analysis for Unseen Data in FrameNet. RANLP2011. pdf
- Michaela Regneri, Alexander Koller, Josef Ruppenhofer and Manfred Pinkal. Learning Script Participants from Unlabeled Data. RANLP2011. pdf
- Manfred Klenner and Don Tuggener. An Incremental Entity-Mention Model for Coreference Resolution with Restrictive Antecedent Accessibility. RANLP2011. pdf
- Ziheng Lin, Hwee Tou Ng and Min-Yen Kan. Automatically Evaluating Text Coherence Using Discourse Relation. ACL 2011. pdf
- Ziheng Lin, Hwee Tou Ng, and Min-Yen Kan. A PDTB-Styled End-to-End Discourse Parser. 2010. pdf
- Annie Louis, Rashmi Prasad, Aravind Joshi and Ani Nenkova. Using Entity Features to Classify Implicit Discourse Relations. SIGDIAL 2010. pdf
- Aria Haghighi and Dan Klein. Coreference Resolution in a Modular, Entity-Centered Model. NAACL-HLT 2010. pdf
- Emily Pitler, Annie Louis and Ani Nenkova. Automatic sense prediction for implicit discourse relations in text. ACL-IJCNLP 2009. pdf
- Rajen Subba and Barbara Di Eugenio. An effective Discourse Parser that uses Rich Linguistic Information. NAACL-HLT 2009. pdf
- Ravikiran Vadlapudi, Poornima Malepati and Suman Yelati. Hierarchical Discourse Parsing Based on Similarity Metrics. RANLP 2009. pdf
- Manfred Klenner, Étienne Ailloud. Optimization in Coreference Resolution is not Needed: A Nearly-Optimal Algorithm with Intensional Constraints. EACL 2009. pdf
- Jason Baldridge and Alex Lascarides. Probabilistic Head-Driven Parsing for Discourse Structure. CoNLL 2005. pdf
- Daniel Marcu and Abdessamad Echihabi. An Unsupervised Approach to Recognizing Discourse Relations. ACL 2002. pdf
Plan Recognition †
- Parag Singla and Raymond J. Mooney. Abductive Markov Logic for Plan Recognition. AAAI2011. pp 1069-1075. pdf
- Nate Blaylock and James Allen. Hierarchical Instantiated Goal Recognition. MOO2006. pdf
- Nate Blaylock and James Allen. Fast Hierarchical Goal Schema Recognition. AAAI2006. pdf
- Douglas E. Appelt and Martha E. Pollack. Weighted Abduction for Plan Ascription. Technical Note 491, SRI International, 1992. pdf
- Sandra Carberry. Techniques for Plan Recognition. User Modeling and User-Adapted Interaction, 11(1-2), pp. 31-48, 2001. pdf
Corpus †
- Penn Discourse Treebank
- RST Discourse Treebank
- Discourse Graphbank: paper LDC
- SDRT annotations of dialogues: DISCOR project
Knowledge Acquisition †
- Doo Soon Kim and Bruce Poter. Integrating declarative knowledge : Issues, Algorithms and Future Work. AAAI2008. pdf
- Jonathan Berant, Tel Aviv and Jacob Goldberger. Global Learning of Typed Entailment Rules. ACL2011. (to appear) pdf
- Stefan Schoenmackers, Jesse Davis, Oren Etzioni and Daniel Weld. Learning First-Order Horn Clauses from Web Text. EMNLP2010. pdf
- Nathanael Chambers and Dan Jurafsky. Unsupervised Learning of Narrative Schemas and their Participants. ACL2010. pdf
Lectures †
- University of Southern California: Introduction to NLP, Empirical Methods in Natural Language Processing
- MIT: Computational Models of Discourse
- Tohoku University: http://www.is.tohoku.ac.jp/_eng/introduction/laboratories/sis/iis_cs.html
- Story Understanding Resources
- David Poole and Alan Mackworth. Artificial Intelligence: Foundations of Computational Agents
Tools †
Misc. †
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