Strategies for Improving the Efficacy of Fusion Question Answering Systems

Web search engines typically retrieve a large number of web pages and overload business analysts with irrelevant information. One approach that has been proposed for overcoming some of these problems is automated Question Answering (QA). This paper describes a case study that was designed to determi...

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Bibliographic Details
Published in:International journal of business intelligence research 2011-01, Vol.2 (1), p.46-63
Main Authors: Schymik, Gregory, St. Louis, Robert, Robles-Flores, José Antonio, Smith-David, Julie
Format: Article
Language:English
Subjects:
Algorithms
Automatic text analysis
Business
Case studies
Database searching
Effectiveness
Intelligence
Internet/Web search services
Keywords
Lists
Online searching
Pattern recognition
Question answering systems
Questions
Search engines
Sourcing
Strategy
Web sites
Websites
Citations: Items that this one cites
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Summary:Web search engines typically retrieve a large number of web pages and overload business analysts with irrelevant information. One approach that has been proposed for overcoming some of these problems is automated Question Answering (QA). This paper describes a case study that was designed to determine the efficacy of QA systems for generating answers to original, fusion, list questions (questions that have not previously been asked and answered, questions for which the answer cannot be found on a single web site, and questions for which the answer is a list of items). Results indicate that QA algorithms are not very good at producing complete answer lists and that searchers are not very good at constructing answer lists from snippets. These findings indicate a need for QA research to focus on crowd sourcing answer lists and improving output format.
ISSN:1947-3591
1947-3605
DOI:10.4018/jbir.2011010104