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Semantic Modelling of User Interests Based on Cross-Folksonomy Analysis

Authors: Szomszor, Martin; Alani, Harith; Cantador, Ivan; O'Hara, Kieron; Shadbolt, Nigel;

Semantic Modelling of User Interests Based on Cross-Folksonomy Analysis

Abstract

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combined.

This research has been supported by the TAGora project funded by the Future and Emerging Technologies program (IST-FET) of the European Commission under the contract IST-34721. The information provided is the sole responsibility of the authors and does not reflect the Commission’s opinion. The Commission is not responsible for any use that may be made of data appearing in this publication

Proceedings of 7th International Semantic Web Conference, ISWC 2008, Karlsruhe, Germany, October 26-30, 2008.

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-88564-1_40

Keywords

Informática, Computer Communication Networks, Data Mining and Knowledge Discovery, Multimedia Information Systems, Logics and Meanings of Programs, Information Systems Applications

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    78
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
78
Top 10%
Top 1%
Top 10%
Green
bronze