K2Q: Generating Natural Language Questions from Keywords with User Refinements
Venue
Proceedings of the 5th International Joint Conference on Natural Language Processing, ACL (2011), 947–955
Publication Year
2011
Authors
Zhicheng Zheng, Xiance Si, Edward Y. Chang, Xiaoyan Zhu
BibTeX
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 de- scribe 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.
