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A Study of User Profile Generation from Folksonomies

A Study of User Profile Generation from Folksonomies
A Study of User Profile Generation from Folksonomies
Recommendation systems which aim at providing relevant information to users are becoming more and more important and desirable due to the enormous amount of information available on the Web. Crucial to the performance of a recommendation system is the accuracy of the user profiles used to represent the interests of the users. In recent years, popular collaborative tagging systems such as del.icio.us have aggregated an abundant amount of user-contributed metadata which provides valuable information about the interests of the users. In this paper, we present our analysis on the personal data in folksonomies, and investigate how accurate user profiles can be generated from this data. We reveal that the majority of users possess multiple interests, and propose an algorithm to generate user profiles which can accurately represent these multiple interests. We also discuss how these user profiles can be used for recommending Web pages and organising personal data.
collaborative tagging, folksonomy, personomy, user profile
Au Yeung, Ching Man
c83390b1-d3a1-459e-8f09-01c81576e066
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Au Yeung, Ching Man
c83390b1-d3a1-459e-8f09-01c81576e066
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

Au Yeung, Ching Man, Gibbins, Nicholas and Shadbolt, Nigel (2008) A Study of User Profile Generation from Folksonomies. Social Web and Knowledge Management, Social Web 2008 Workshop at WWW2008, China. 21 - 25 Apr 2008. (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Recommendation systems which aim at providing relevant information to users are becoming more and more important and desirable due to the enormous amount of information available on the Web. Crucial to the performance of a recommendation system is the accuracy of the user profiles used to represent the interests of the users. In recent years, popular collaborative tagging systems such as del.icio.us have aggregated an abundant amount of user-contributed metadata which provides valuable information about the interests of the users. In this paper, we present our analysis on the personal data in folksonomies, and investigate how accurate user profiles can be generated from this data. We reveal that the majority of users possess multiple interests, and propose an algorithm to generate user profiles which can accurately represent these multiple interests. We also discuss how these user profiles can be used for recommending Web pages and organising personal data.

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More information

Accepted/In Press date: 1 March 2008
Additional Information: Event Dates: April 21-25, 2008
Venue - Dates: Social Web and Knowledge Management, Social Web 2008 Workshop at WWW2008, China, 2008-04-21 - 2008-04-25
Keywords: collaborative tagging, folksonomy, personomy, user profile
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 265222
URI: https://eprints.soton.ac.uk/id/eprint/265222
PURE UUID: 4f2b8ed6-4f06-447c-96f7-c5242cad15e7
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956

Catalogue record

Date deposited: 28 Feb 2008 22:31
Last modified: 06 Jun 2018 12:55

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Contributors

Author: Ching Man Au Yeung
Author: Nicholas Gibbins ORCID iD
Author: Nigel Shadbolt

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