Mining world knowledge for analysis of search engine content

Little is known about the content of the major search engines. We present an automatic learning method which trains an ontology with world knowledge of hundreds of different subjects in a three-level taxonomy covering the documents offered in our university library. We then mine this ontology to fin...

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Bibliographic Details
Published inWeb intelligence and agent systems Vol. 5; no. 3; pp. 233 - 253
Main Authors King, John D., Li, Yuefeng, Tao, Xiaohui, Nayak, Richi
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.08.2007
Subjects
search engines
hierarchal classification
taxonomy
collection selection
Ontology
data mining
Online AccessGet full text
ISSN1570-1263
1875-9289
DOI10.3233/WEB-2007-wia00115

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Summary:Little is known about the content of the major search engines. We present an automatic learning method which trains an ontology with world knowledge of hundreds of different subjects in a three-level taxonomy covering the documents offered in our university library. We then mine this ontology to find important classification rules, and then use these rules to perform an extensive analysis of the content of the largest general purpose internet search engines in use today. Instead of representing documents and collections as a set of terms, we represent them as a set of subjects, which is a highly efficient representation, leading to a more robust representation of information and a decrease of synonymy.
ISSN:1570-1263
1875-9289
DOI:10.3233/WEB-2007-wia00115