Personalization with dynamic group profile

Kamal Taha, Ramez Elmasri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose an XML-based recommender system, called PDGP. It is a type of collaborative information filtering system. PDGP uses ontology-driven social networks, where nodes represent social groups. A social group is an entity that defines a group based on demographic, ethnic, cultural, religious, age, or other characteristics. In the PDGP framework, query results are filtered and ranked based on the preferences of the social groups to which the user belongs. The user's social groups are inferred implicitly by the system without involving the user. PDGP constructs the social groups and identifies their preferences dynamically on the fly. These preferences are determined from the preferences of the social groups' member users using a group modeling strategy. PDGP can be used for various practical applications, such as Internet or other businesses that market preference-driven products. We experimentally compared PDGP with an existing system. Results showed marked improvement.

Original languageBritish English
Title of host publicationProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages488-492
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey
Duration: 26 Aug 201229 Aug 2012

Publication series

NameProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

Conference

Conference2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Country/TerritoryTurkey
CityIstanbul
Period26/08/1229/08/12

Keywords

  • Group profile
  • Personalization
  • Recommender system

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