Paper Info
Title
QuASM: a system for question answering using semi-structured data
Abstract
This paper describes a system for question answering using semi-structured metadata, QuASM (pronounced "chasm"). Question answering systems aim to improve search performance by providing users with specific answers, rather than having users scan retrieved documents for these answers. Our goal is to answer factual questions by exploiting the structure inherent in documents found on the World Wide Web (WWW). Based on this structure, documents are indexed into smaller units and associated with metadata. Transforming table cells into smaller units associated with metadata is an important part of this task. In addition, we report on work to improve question classification using language models. The domain used to develop this system is documents retrieved from a crawl of www.fedstats.gov.
Year
DOI
Venue
2002
10.1145/544220.544228
JCDL
Keywords
Field
DocType
question classification,language model,factual question,semi-structured data,transforming table cell,smaller unit,semi-structured metadata,question answering,important part,world wide web,question answering system,semi structured data,document retrieval,indexation,metadata
Semi-structured data,Metadata,Metadata repository,World Wide Web,Question answering,Information retrieval,Computer science,Language model
Conference
ISBN
Citations 
PageRank 
1-58113-513-0
49
3.86
References 
Authors
7
7
Name
Order
Citations
PageRank
David Pinto124519.82
Michael Branstein2493.86
Ryan Coleman3504.23
W. Bruce Croft4178122796.94
Matthew King5645.95
Wei Li631830.46
Xing Wei7114160.87