Passage Selection To Improve Question Answering

Boosting Passage Retrieval through Reuse in Question Answering

Question Answering (QA) is an emerging important field in Information Retrieval. In a QA system the archive of previous questions asked from the system makes a collection full of useful factual nuggets. This paper makes an initial attempt to investigate the reuse of facts contained in the archive of previous questions to help and gain performance in answering future related factoid questions. I...

Discriminative Information Retrieval for Question Answering Sentence Selection

We propose a framework for discriminative IR atop linguistic features, trained to improve the recall of answer candidate passage retrieval, the initial step in text-based question answering. We formalize this as an instance of linear feature-based IR, demonstrating a 34% 43% improvement in recall for candidate triage for QA.

Component Analysis of a Chinese Factoid Question-Answering System

An analysis is provided for three major components of a simple Chinese Question-Answering system: passage retrieval, entity extraction and candidate selection. The order of least effective component is determined to be: answer selection, retrieval and extraction. In crosslingual QA, deficiencies in question translation not only lead to retrieval loss, but may also have adverse effects at answer...

SiteQ/J: A Question Answering System for Japanese

This paper describes our Question Answering system participated in QAC Task1 of NTCIR3 and reports the results with some observations. Through analyzing the previous TREC QA data, we defined passage and developed passage selection method suitable for Question Answering. Using LexicoSemantic Patterns (LSP), we identify answer type of a question and detect answer candidates without any deep lingu...

Question Answering by Passage Selection (MultiText Experiments for TREC-9)