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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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.

DOI