摘要：Motivated by the continuous growth of the Web in the number of sites and users, several search engines at- tempt to extend their traditional functionality by incorporating question answering (QA) facilities. This ex- tension seems natural but it is not straightforward since current QA systems still achieve poor performance rates for languages other than English. Based on the fact that retrieval effectiveness has been previously improved by combining evidence from multiple search engines, in this paper we propose a method that al- lows taking advantage of the outputs of several QA systems. This method is based on an answer validation approach that decides about the correctness of answers based on their entailment with a support text, and therefore, that reduces the influence of the answer redundancies and the system confidences. Experimental results on Spanish are encouraging; evaluated over a set of 190 questions from the CLEF 2006 collection, our method responded correctly 63% of the questions, outperforming the best QA participating system (53%) by a relative increase of 19%. In addition, when they were considered five answers per question, our method could obtain the correct answer for 73% of the questions. In this case, it outperformed traditional multi-stream techniques by generating a better ranking of the set of answers presented to the users.
关键词：question answering; information fusion; answer validation; textual entailment
