Statistical Machine Translation for Query Expansion in Answer Retrieval
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BibTeX
@MISC{Riezler_statisticalmachine,
author = {Stefan Riezler and Er Vasserman and Ioannis Tsochantaridis and Vibhu Mittal and Yi Liu},
title = {Statistical Machine Translation for Query Expansion in Answer Retrieval},
year = {}
}
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Abstract
We present an approach to query expansion in answer retrieval that uses Statistical Machine Translation (SMT) techniques to bridge the lexical gap between questions and answers. SMT-based query expansion is done by i) using a full-sentence paraphraser to introduce synonyms in context of the entire query, and ii) by translating query terms into answer terms using a full-sentence SMT model trained on question-answer pairs. We evaluate these global, context-aware query expansion techniques on tfidf retrieval from 10 million question-answer pairs extracted from FAQ pages. Experimental results show that SMTbased expansion improves retrieval performance over local expansion and over retrieval without expansion. 1
