论文信息 - Exploiting the Use of Prior Probabilities for Passage Retrieval in Question Answering

Exploiting the Use of Prior Probabilities for Passage Retrieval in Question Answering

Document Retrieval assumes that a document is independent of its relevance, and non-relevance. Previous works showed that the same assumption is being considered for passage retrieval in the context of Question Answering. In this paper, we relax this assumption and describe a method for estimating the prior of a passage being relevant, and non-relevant to a question. These prior probabilities are used in the process of ranking passages. We also describe a trivial method for identifying relevant and nonrelevant text to a question using the Web and AQUAINT corpus as information sources. An empirical evaluation on TREC 2006 Question Answering test set showed that in the context of Question Answering prior probabilities are necessary in ranking the passages.

Vasudeva Varma | Surya Ganesh Veeravalli

[1] Hoa Trang Dang,et al. Overview of the TREC 2006 Question Answering Track 99 , 2006, TREC.

[2] Mats Rooth,et al. Looking Under the Hood : Tools for Diagnosing your Question Answering Engine , 2001, ACL 2001.

[3] Dan Klein,et al. Accurate Unlexicalized Parsing , 2003, ACL.

[4] Robert J. Gaizauskas,et al. Evaluating Passage Retrieval Approaches for Question Answering , 2004, ECIR.

[5] Claudio Carpineto,et al. An information-theoretic approach to automatic query expansion , 2001, TOIS.

[6] John D. Lafferty,et al. Model-based feedback in the language modeling approach to information retrieval , 2001, CIKM '01.

[7] Vasudeva Varma,et al. Capturing Sentence Prior for Query-Based Multi-Document Summarization , 2007, RIAO.

[8] Dan Klein,et al. Fast Exact Inference with a Factored Model for Natural Language Parsing , 2002, NIPS.

[9] ChengXiang Zhai,et al. Probabilistic Relevance Models Based on Document and Query Generation , 2003 .

[10] W. Bruce Croft,et al. Passage retrieval based on language models , 2002, CIKM '02.

[11] W. Bruce Croft,et al. A Translation Model for Sentence Retrieval , 2005, HLT.

[12] Thomas M. Cover,et al. Elements of Information Theory , 2005 .

[13] S. Robertson. The probability ranking principle in IR , 1997 .