User Modeling Based on Emergent Domain Semantics

In this paper we present an approach to user modeling based on the domain model that we generate automatically by resource (text) content processing and analysis of associated tags from a social annotation service User's interests are modeled by overlaying the domain model – via keywords extracted from resource's (text) content, and tags assigned by the user or other (similar) users The user model is derived automatically We combine content- and tag-based approaches, shifting our approach beyond flat “folksonomical” representation of user interests to involve relationships between both keywords and tags.

[1]  Mária Bieliková,et al.  Automatic Concept Relationships Discovery for an Adaptive E-course , 2009, EDM.

[2]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[3]  Pavol Navrat,et al.  A Simple Personalization Layer Improving Relevancy of Web Search , 2009 .

[4]  Federica Cena,et al.  Towards a Tag-Based User Model: How Can User Model Benefit from Tags? , 2007, User Modeling.

[5]  Alfred Kobsa,et al.  The Adaptive Web, Methods and Strategies of Web Personalization , 2007, The Adaptive Web.

[6]  Cristina Conati,et al.  User Modeling 2007, 11th International Conference, UM 2007, Corfu, Greece, June 25-29, 2007, Proceedings , 2007, User Modeling.

[7]  Peter Brusilovsky,et al.  Methods and techniques of adaptive hypermedia , 1996, User Modeling and User-Adapted Interaction.

[8]  Peter Brusilovsky,et al.  Adaptive Hypermedia , 2001, User Modeling and User-Adapted Interaction.

[9]  Shinichi Honiden,et al.  Web Page Recommender System based on Folksonomy Mining for ITNG ’06 Submissions , 2006, Third International Conference on Information Technology: New Generations (ITNG'06).

[10]  Zdenek Zdrahal,et al.  Towards a framework for comparing automatic term recognition methods , 2009 .

[11]  Georgia Koutrika,et al.  Can social bookmarking improve web search? , 2008, WSDM '08.

[12]  Mária Bieliková,et al.  Automated Educational Course Metadata Generation Based on Semantics Discovery , 2009, EC-TEL.

[13]  Reyn NakamotoShinsuke,et al.  Tag-Based Contextual Collaborative Filtering , 2007 .