Answer typing for information retrieval
Venue
Proceeding of the 18th ACM conference on Information and knowledge management (CIKM), ACM, Hong Kong (2009), pp. 1955-1958
Publication Year
2009
Authors
Christopher Pinchak, Davood Rafiei, Dekang Lin
BibTeX
Abstract
Answer typing is commonly thought of as finding appropriate responses to given
questions. We extend the notion of answer typing to information retrieval to ensure
results contain plausible answers to queries. Identification of a large class of
applicable queries is performed using a discriminative classifier, and
discriminative preference ranking methods are employed for the selection of
type-appropriate terms. Experimental results show that type-appropriate terms
identified by the model are superior to terms most commonly associated with the
query, providing strong evidence that answer typing techniques can find meaningful
and appropriate terms. Further experiments show that snippets containing correct
answers are ranked higher by our model than by the baseline Google search engine in
those instances in which a query does indeed seek a short answer.
