Generating Natural Language Questions from Keywords with User Refinements
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.