JOURNAL ARTICLE

Question Answering using Integrated Information Retrieval and Information Extraction

Barry SchiffmanKathleen McKeown

Year: 2007 Journal:   Columbia Academic Commons (Columbia University) Pages: 532-539   Publisher: Columbia University

Abstract

This paper addresses the task of providing extended responses to questions regarding specialized topics. This task is an amalgam of information retrieval, topical summarization, and Information Extraction (IE). We present an approach which draws on methods from each of these areas, and compare the effectiveness of this approach with a query-focused summarization approach. The two systems are evaluated in the context of the prosecution queries like those in the DARPA GALE distillation evaluation.

Keywords:
Automatic summarization Computer science Information retrieval Task (project management) Information extraction Question answering Context (archaeology) Multi-document summarization Engineering

Metrics

27
Cited By
4.27
FWCI (Field Weighted Citation Impact)
10
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems
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