Publikation
Learning to Rank Effective Paraphrases from Query Logs for Community Question Answering
Alejandro Figueroa; Günter Neumann
In: Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13) . AAAI Conference on Artificial Intelligence (AAAI-13), 27th, July 14-18, Bellevue, WA, USA, AAAI, 7/2013.
Zusammenfassung
We present a novel method for ranking query paraphrases
for effective search in community question answering
(cQA). The method uses query logs from Yahoo!
Search and Yahoo! Answers for automatically extracting
a corpus of paraphrases of queries and questions
using the query-question click history. Elements of
this corpus are automatically ranked according to recall
and mean reciprocal rank, and then used for learning
two independent learning to rank models (SVMRank),
whereby a set of new query paraphrases can be scored
according to recall and MRR. We perform several automatic
evaluation procedures using cross-validation for
analyzing the behavior of various aspects of our learned
ranking functions, which show that our method is useful
and effective for search in cQA.