Authors:
Garofalakis John
and
Oikonomou Flora
Affiliation:
Patras University, Greece
Keyword(s):
Semantic Clustering, Ontology, User Profiles, Dietary Profiles, Web Search, Personalization, Web Usage Mining, Information Search and Retrieval.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
The World Wide Web has become a huge data repository and it keeps growing exponentially, whereas the human capability to find, process and understand the provided content remains constant. Search engines facilitate the search process in the WWW and they have become an integral part of the web users' daily lives. However users are characterized by different needs, preferences and special characteristics, navigate through large Web structures and may lost their goal of inquiry. Web personalization is one of the most promising approaches for alleviating information overload providing tailored navigation experiences to Web users. This paper presents the methodology which was implemented in order to personalize a search engine’s results for corresponding users’ preferences and dietary characteristics. This methodology was implemented in two parts. The online part uses a search engines’ log files and the dietary characteristics of the users in order to extract information for their prefere
nces. With the use of an ontology and a clustering algorithm, semantic profiling of users’ interests is achieved. In the online part the methodology re-ranks the search engines’ results. Experimental evaluation of the presented methodology shows that the expected objectives from the semantic users’ clustering in search engines are achievable.
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