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Enriching ontological user profiles with tagging history for multi-domain recommendations

Cantador, Iván; Szomszor, Martin; Alani, Harith; Fernandez, Miriam and Castells, Pablo (2008). Enriching ontological user profiles with tagging history for multi-domain recommendations. In: 1st International Workshop on Collective Semantics: Collective Intelligence & the Semantic Web (CISWeb 2008), 2 Jun 2008, Tenerife, Spain.

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Many advanced recommendation frameworks employ ontologies of various complexities to model individuals and items, providing a mechanism for the expression of user interests and the representation of item attributes. As a result, complex matching techniques can be applied to support individuals in the discovery of items according to explicit and implicit user preferences. Recently, the rapid adoption of Web2.0, and the proliferation of social networking sites, has resulted in more and more users providing an increasing amount of information about themselves that could be exploited for recommendation purposes. However, the unification of personal information with ontologies using the contemporary knowledge representation methods often associated with Web2.0 applications, such as community tagging, is a non-trivial task. In this paper, we propose a method for the unification of tags with ontologies by grounding tags to a shared representation in the form of Wordnet and Wikipedia. We incorporate individuals' tagging history into their ontological profiles by matching tags with ontology concepts. This approach is preliminary evaluated by extending an existing news recommendation system with user tagging histories harvested from popular social networking sites.

Item Type: Conference or Workshop Item
Copyright Holders: 2008 The authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetThe European Commission (FP6-027685 � MESH, IST-34721 � TAGora)
Keywords: social tagging; web 2.0; ontology; semantic web; user modelling; recommender systems
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 20015
Depositing User: Harith Alani
Date Deposited: 08 Apr 2010 10:29
Last Modified: 09 Dec 2018 04:38
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