Personalised video retrieval: application of implicit feedback and semantic user profiles

Hopfgartner, F. (2010) Personalised video retrieval: application of implicit feedback and semantic user profiles. ACM SIGMM Records, 2(4), pp. 6-7. (doi: 10.1145/2039331.2039334)

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Publisher's URL: http://dx.doi.org/10.1145/2039331.2039334

Abstract

A challenging problem in the user profiling domain is to create profiles of users of retrieval systems. This problem even exacerbates in the multimedia domain. Due to the Semantic Gap, the difference between lowlevel data representation of videos and the higher concepts users associate with videos, it is not trivial to understand the content of multimedia documents and to find other documents that the users might be interested in. A promising approach to ease this problem is to set multimedia documents into their semantic contexts. The semantic context can lead to a better understanding of the personal interests. Knowing the context of a video is useful for recommending users videos that match their information need. By exploiting these contexts, videos can also be linked to other, contextually related videos. From a user profiling point of view, these links can be of high value to recommend semantically related videos, hence creating a semantic-based user profile. This thesis introduces a semantic user profiling approach for news video retrieval, which exploits a generic ontology to put news stories into its context.

Item Type:Articles
Status:Published
Refereed:No
Glasgow Author(s) Enlighten ID:Hopfgartner, Dr Frank
Authors: Hopfgartner, F.
College/School:College of Arts & Humanities > School of Humanities > Information Studies
Journal Name:ACM SIGMM Records
Publisher:ACM
ISSN:1947-4598

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