Personal tools
You are here: Home → Knowledge Base → Personal content recommender based on a hierarchical user model for the selection of TV programmes  

Personal content recommender based on a hierarchical user model for the selection of TV programmes

Main information
In this paper we present our approach to user modeling for a personalized selection of multimedia content tested on a corpus of TV programmes. The idea of this approach is to classify content (TV programmes) based on the calculation of similarities between the description of content and the user model for each descrip- tion attribute. Calculated similarities are then combined into a classi¯cation decision using the Support Vector Machines. The basis for the calculation of similarities is a hierarchical structure of the user model, overlaid upon a taxonomy of TV pro- gramme genres. Preliminary results show that it works well with a varying quality of content descriptions including incomplete genre classi¯cation and arbitrary number of description attributes. The evaluation of the system performance was based on content described using the TV-Anytime standard, but the approach can be adapted for search of other types of content with multi-attribute descriptions. 
WP6: Personalisation and Feedback. 
University of Ljubljana  Matevz Pogacnik 
2007-03-15 13:43  Request for more detail


Access and Use Rights
For LIVE project internal research purposes only. 
Copyright University of Ljubljana. 
 
Closed, attachment is not public 


This item is not available for public download. For further information click on Request for more details above

LIVE's knowledge base
  • What is available here?

Here you can search and access the documented work of the LIVE project. Documents include the official reporting of the project's work known as "deliverables", scientific and technical publications, study reports, press material, presentation material  as well as IPR pending material.

  • How can I access the material?

You can search this knowledge base by project partner, work area or key words.

By simply clicking "all" the complete list of documents will be listed.

  • Is everything open to the public?

Please note that only those publications marked in green have been cleared for immediate public access. To request access to those publications not open please click on the "request for more detail" link in the relevant document. Your request will be automatically sent to the authors for consideration.