Answer models for question answering passage retrieval

Answer patterns have been shown to improve the performance of open-domain factoid QA systems. Their use, however, requires either constructing the patterns manually or developing algorithms for learning them automatically. We present here a simpler approach that extends the techniques of language modeling to create answer models. These are language models trained on the correct answers to training questions. We show how they fit naturally into a probabilistic model for answer passage retrieval and demonstrate their effectiveness on the TREC 2002 QA Corpus. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—Retrieval Models General Terms Algorithms, Experimentation Keywords Question Answering Systems, Language Models, Answer Passage Retrieval, Open Domain Factoid Questions

• Type: Conference
• Year: 2004
• Where: SIGIR
• Authors: Andrés Corrada-Emmanuel, W. Bruce Croft
• Keywords: Answer Passage Retrieval, Language Models, Open-domain Factoid Qa, SIGIR 2004