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Social Search and Personalization Through Demographic Filtering

Social Search and Personalization Through Demographic Filtering
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Author(s): Kamal Taha (Khalifa University, UAE) and Ramez Elmasri (University of Texas at Arlington, USA)
Copyright: 2012
Pages: 21
Source title: Social Network Mining, Analysis, and Research Trends: Techniques and Applications
Source Author(s)/Editor(s): I-Hsien Ting (National University of Kaohsiung, Taiwan), Tzung-Pei Hong (National University of Kaohsiung, Taiwan) and Leon Shyue-Liang Wang (National University of Kaohsiung, Taiwan)
DOI: 10.4018/978-1-61350-513-7.ch012

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Abstract

Most existing personalized search systems do not consider group profiling. Group profiling can be an efficient retrieval mechanism, where a user profile is inferred from the profile of the social groups to which the user belongs. The authors propose an XML search system called DemoFilter which employs the concept of group profiling. DemoFilter simplifies the personalization process by pre-defining various categories of social groups and then identifying their preferences. Social groups are characterized based on demographic, ethnic, cultural, religious, age, or other characteristics. DemoFilter can be used for various practical applications, such as Internet or other businesses that market preference-driven products. In the ontology, the preferences of a social group are identified from published studies about the social group. They experimentally evaluate the search effectiveness of DemoFilter and compare it to an existing search engine.

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