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Rule Generation Based On Structural Clustering For Automatic Question Answering

In rule-based methods for Question-Answering (QA) research, typical rule discovery techniques are based on structural pattern overlapping and lexical information. These usually result in rules that may require further interpretation and rules that may be redundant. To address these issues, an automa...

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Main Author: Song , Shen
Format: Thesis
Language:English
Published: 2009
Subjects:
QA75.5-76.95 Electronic computers. Computer science
Online Access:http://eprints.usm.my/42706/1/SONG_SHEN.pdf
http://eprints.usm.my/42706/
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spelling my.usm.eprints.42706 http://eprints.usm.my/42706/ Rule Generation Based On Structural Clustering For Automatic Question Answering Song , Shen QA75.5-76.95 Electronic computers. Computer science In rule-based methods for Question-Answering (QA) research, typical rule discovery techniques are based on structural pattern overlapping and lexical information. These usually result in rules that may require further interpretation and rules that may be redundant. To address these issues, an automatic structural rule generation algorithm is presented via clustering, where a center sentence-based clustering method is designed to automatically generate rules for QA systems. 2009-12 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/42706/1/SONG_SHEN.pdf Song , Shen (2009) Rule Generation Based On Structural Clustering For Automatic Question Answering. Masters thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA75.5-76.95 Electronic computers. Computer science
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Song , Shen
Rule Generation Based On Structural Clustering For Automatic Question Answering
description In rule-based methods for Question-Answering (QA) research, typical rule discovery techniques are based on structural pattern overlapping and lexical information. These usually result in rules that may require further interpretation and rules that may be redundant. To address these issues, an automatic structural rule generation algorithm is presented via clustering, where a center sentence-based clustering method is designed to automatically generate rules for QA systems.
format Thesis
author Song , Shen
author_facet Song , Shen
author_sort Song , Shen
title Rule Generation Based On Structural Clustering For Automatic Question Answering
title_short Rule Generation Based On Structural Clustering For Automatic Question Answering
title_full Rule Generation Based On Structural Clustering For Automatic Question Answering
title_fullStr Rule Generation Based On Structural Clustering For Automatic Question Answering
title_full_unstemmed Rule Generation Based On Structural Clustering For Automatic Question Answering
title_sort rule generation based on structural clustering for automatic question answering
publishDate 2009
url http://eprints.usm.my/42706/1/SONG_SHEN.pdf
http://eprints.usm.my/42706/
_version_ 1643710553016762368
score 13.159267

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