Answer typing is an important aspect of the question answering process. Most commonly addressed with the use of a fixed set of possible answer classes via question classification, answer typing influences which answers will ultimately be selected as correct. Answer typing introduces the concept of type-appropriate responses. Such responses are plausible in the context of question answering when they are believable as answers to a given question. This notion of type-appropriateness is distinct from correctness, as there may exist many type-appropriate responses that are not correct answers. Type-appropriate responses can even exist for other kinds of queries that are not strictly questions.
This work introduces class-free models of answer type for certain kinds of questions as well as models of type-appropriateness useful to the domain of information retrieval. Models built for both open-ended noun phrase questions and how-adjective questions are designed to evaluate the type-appropriateness of a candidate answer directly rather than via the use of an intermediary question class (as is done with question classification). Experiments show a meaningful improvement over alternative typing strategies for these kinds of questions. Ideas from these models are then applied outside of the domain of question answering in an effort to improve traditional information retrieval results. Experiments comparing reranked results with those of the Google search engine show improvements are made in those rare situations for which Google provides less than ideal results.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/426 |
| Date | 11 1900 |
| Creators | Pinchak, Christopher |
| Contributors | Lin, Dekang (Computing Science), Rafiei, Davood (Computing Science), Lin, Dekang (Computing Science), Rafiei, Davood (Computing Science), Kondrak, Grzegorz (Computing Science), Nascimento, Mario (Computing Science), Shiri, Ali (Library and Information Studies), Srihari, Rohini (Computer Science, State University of New York at Buffalo) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 555303 bytes, application/pdf |
| Relation | Pinchak, Christopher and Lin, Dekang (2006). A Probabilistic Answer Type Model. Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2006), pages 393 - 400., Pinchak, Christopher and Bergsma, Shane (2007). Automatic Answer Typing for How-Questions. Proceedings of Human Language Technologies 2007 and the Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL 2007), pages pages 516 - 523., Pinchak, Christopher, Lin, Dekang, and Rafiei, Davood (2009). Flexible Answer Typing with Discriminative Preference Ranking. Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2009), pages 666 - 674. |
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