Exploiting the Use of Prior Probabilities for Passage Retrieval in Question Answering
Surya Ganesh, Vasudeva Varma · 2009
Document Retrieval assumes that a document is independent of its relevance, and non-relevance. Previous works showed that the same assump-tion is being considered for passage retrieval in the context of Question Answering. In this pa-per, 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 pro-cess of ranking passages. We also describe a trivial method for identifying relevant and non-relevant 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 nec-essary in ranking the passages. 1