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dc.contributor.authorKhoo, Christopher S.G.
dc.contributor.authorNg, Karen
dc.contributor.authorOu, Shiyan
dc.contributor.editorLópez-Huertas, Marí­a J.en_US
dc.date.accessioned2006-08-14T00:00:01Z
dc.date.available2010-06-18T23:39:00Z
dc.date.issued2002en_US
dc.date.submitted2006-08-14en_US
dc.identifier.citationAn exploratory study of human clustering of Web pages 2002, :351-357en_US
dc.identifier.urihttp://hdl.handle.net/10150/106057
dc.description.abstractThis study seeks to find out how human beings cluster Web pages naturally. 20 Web pages retrieved by the Northern Light search engine for each of 10 queries were sorted by 3 subjects into categories that were natural or meaningful to them. It was found that different subjects clustered the same set of Web pages quite differently and created different categories. The average inter-subject similarity of the clusters created was a low 0.27. Subjects created an average of 5.4 clusters for each sorting. The categories constructed can be divided into 10 types. About 1/3 of the categories created were topical. Another 20% of the categories relate to the degree of relevance or usefulness. The rest of the categories were subject-independent categories such as format, purpose, authoritativeness and direction to other sources. The authors plan to develop automatic methods for categorizing Web pages using the common categories created by the subjects. It is hoped that the techniques developed can be used by Web search engines to automatically organize Web pages retrieved into categories that are natural to users.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherErgon-Verlagen_US
dc.subjectCognitive Scienceen_US
dc.subjectKnowledge Organizationen_US
dc.subjectUser Studiesen_US
dc.subject.otherhuman categorizationen_US
dc.subject.otherweb pagesen_US
dc.titleAn exploratory study of human clustering of Web pagesen_US
dc.typeConference Paperen_US
refterms.dateFOA2018-04-26T10:27:38Z
html.description.abstractThis study seeks to find out how human beings cluster Web pages naturally. 20 Web pages retrieved by the Northern Light search engine for each of 10 queries were sorted by 3 subjects into categories that were natural or meaningful to them. It was found that different subjects clustered the same set of Web pages quite differently and created different categories. The average inter-subject similarity of the clusters created was a low 0.27. Subjects created an average of 5.4 clusters for each sorting. The categories constructed can be divided into 10 types. About 1/3 of the categories created were topical. Another 20% of the categories relate to the degree of relevance or usefulness. The rest of the categories were subject-independent categories such as format, purpose, authoritativeness and direction to other sources. The authors plan to develop automatic methods for categorizing Web pages using the common categories created by the subjects. It is hoped that the techniques developed can be used by Web search engines to automatically organize Web pages retrieved into categories that are natural to users.


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