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Class-free answer typing

  • Author / Creator
    Pinchak, Christopher
  • 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.

  • Subjects / Keywords
  • Graduation date
    2009-11
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3ZS3M
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Lin, Dekang (Computing Science)
    • Rafiei, Davood (Computing Science)
  • Examining committee members and their departments
    • Nascimento, Mario (Computing Science)
    • Rafiei, Davood (Computing Science)
    • Lin, Dekang (Computing Science)
    • Kondrak, Grzegorz (Computing Science)
    • Shiri, Ali (Library and Information Studies)
    • Srihari, Rohini (Computer Science, State University of New York at Buffalo)