期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：9
页码：3686-3690
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Web-page recommendation plays a vital role in intelligent Web systems. Useful knowledge dis covery from Web usage data and satisfactory knowledge representation for effective Web-page recommendations are crucial and challenging work. Here we introduce a method to efficiently provide better Web-page recommendation generations through semantic-enhancement by integrating the domain and Web usage knowledge of a website. The models are proposed to represent the domain knowledge. This model uses ontology to represent the domain knowledge. This model uses one automatically generated semantic network to represent domain terms, Web-pages, and the relations between them. Another new model, the conceptual prediction model is proposed to automatically generate a semantic network of the semantic Web usage knowledge, which is the integration of domain knowledge and Web usage knowledge. A number of effective queries have been developed to query about these knowledge bases. Based on these queries, a set of recommendation strategies have been proposed to generate Web-page candidates. A key information extraction algorithm will be developed to compare with the term extraction method in this work, and perform intense comparisons with the existing semantic Web-page recommendation systems.
