K2Q : generating natural language questions from keywords with user refinements
Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
Asian Federation of Natural Language Processing (AFNLP)
Abstract
Garbage in and garbage out. A Q&A system
must receive a well formulated question
that matches the user’s intent or she
has no chance to receive satisfactory answers.
In this paper, we propose a keywords
to questions (K2Q) system to assist
a user to articulate and refine questions.
K2Q generates candidate questions and refinement
words from a set of input keywords.
After specifying some initial keywords,
a user receives a list of candidate
questions as well as a list of refinement
words. The user can then select a satisfactory
question, or select a refinement word
to generate a new list of candidate questions
and refinement words. We propose
a User Inquiry Intent (UII) model to describe
the joint generation process of keywords
and questions for ranking questions,
suggesting refinement words, and generating
questions that may not have previously
appeared. Empirical study shows UII to be
useful and effective for the K2Q task.
Description
Meeting: 5th International Joint Conference on Natural Language Processing, Chiang Mai, Thailand, November 8 - 13, 2011
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The table of contents for this item can be shared with the requester. The requester may then choose one chapter, up to 10% of the item, as per the Fair Dealing provision of the Canadian Copyright Act
item.page.type
Conference Paper
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Text
Keywords
NATURAL LANGUAGE PROCESSING, QUESTION ANSWER SYSTEMS, SEARCH PROFILES
Citation
Zhicheng Zheng, Xiance Si, Chang, E.Y., & Xiaoyan Zhu (2011). K2Q: Generating Natural Language Questions from Keywords with User Refinements. Proceedings of the 5th International Joint Conference on Natural Language Processing, 947-955.