A Proposed Analysis for User Behavior
This paper presents a model of the “Semantic Web User Behavior Model” (SWUBM). That behavior is an important piece of adaptation and personalization, but it is too complicated to be a part of a generic Model. Semantic Web User behavior differs depending on web type and usages. For example, user behavior model on twitter is not the same on Wikipedia. So, in this thesis the researcher introduces a common general model that fit most of semantic websites.
The researcher uses some modeling features in this paper. Like personal features, content features, and focus features. In the personal features the researcher uses contact information and demographics. Features reductions using rough sets is the used method in minimizing the accumulated results from the semantic web sites. With the K-Means clustering algorithm and neural network.
Keywords: Semantic web, User Behavior, K-Means clustering Modeling.
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ABOUT THE AUTHORS
Tamer Ahmed Abdellatif
Researcher in Faculty of Computers and Information. Mansoura University. Information Systems Department.
Aziza S. Asem
Dr. in Faculty of Computers and Information. Mansoura University. Information Systems Department.
Mahmoud M Abd El-Latif
Ass. Prof in Faculty of Computers and Information. Helwan University. Information Systems Department.
Tamer Ahmed Abdellatif
Researcher in Faculty of Computers and Information. Mansoura University. Information Systems Department.
Aziza S. Asem
Dr. in Faculty of Computers and Information. Mansoura University. Information Systems Department.
Mahmoud M Abd El-Latif
Ass. Prof in Faculty of Computers and Information. Helwan University. Information Systems Department.
