A decision fusion of user page and concept matrices for enhancing next page prediction
作者： Wedad Hussein , Tarek F. Gharib , Rasha M. Ismail , Mostafa G. M. Mostafa
DOI: 10.1109/INFOS.2014.7036712
关键词: Semantics 、 Computer science 、 Semantic Web 、 Cluster analysis 、 Social Semantic Web 、 Web page 、 Focus (computing) 、 Information retrieval 、 Semantic Web Stack 、 Personalization 、 World Wide Web
摘要: With the advances in communication and technologies, World Wide Web is becoming an important rich source for information. The amount variety of information available makes customization personalized recommendations utter importance. In this paper, we present a framework next page prediction that exploits users' access history combined with his semantic interests to generate accurate recommendations. proposed offered 54.3 % improvement accuracy over conventional methods prediction. suggested also employs user clustering focus search which reduced time by 63.4%.
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