期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2011
卷号：2
期号：2
DOI：10.14569/IJACSA.2011.020219
出版社：Science and Information Society (SAI)
摘要：To provide personalized support in on-line course resources system, a semantic web-based personalized learning service is proposed to enhance the learner's learning efficiency. When a personalization system relies solely on usage-based results, however, valuable information conceptually related to what is finally recommended may be missed. Moreover, the structural properties of the web site are often disregarded. In this Paper, we present a personalize Web search system, which can helps users to get the relevant web pages based on their selection from the domain list. In the first part of our work we present Semantic Web Personalization, a personalization system that integrates usage data with content semantics, expressed in ontology terms, in order to compute semantically enhanced navigational patterns and effectively generate useful recommendations. To the best of our knowledge, our proposed technique is the only semantic web personalization system that may be used by non-semantic web sites. In the second part of our work, we present a novel approach for enhancing the quality of recommendations based on the underlying structure of a web site. We introduce UPR (Usage-based Page Rank), a Page Rank-style algorithm that relies on the recorded usage data and link analysis techniques based on user interested domains and user query.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; SemanticWeb Mining;Personalized Recommendation;Recommended System
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