Abstract- Now a day, intelligent recommender systems on the web
intends to recommend web pages for individual users by
discovering useful knowledge from Web usage data and web
content data. Knowledge representation for the web contents and
integrating with web usage knowledge are the challenging issues to
make Web page recommendations effective. This paper presents an
effective method to integrate the domain knowledge and web usage
knowledge of a website through semantics. Perhaps, a new model is
framed to construct a semantic hierarchy of the web log data and
the domain contents, which represents the integrated usage
knowledge and domain knowledge. This model has two phases: first
one is to generate domain knowledge represented with ontology for
the website; second one is to generate mappings between web pages
and domain terms in the ontology based on the usage of an
individual. However this semantically enhanced knowledge
representation uses a recommendation strategy to recommend web
pages dynamically. The recommendation results have been
compared with the results obtained from an advanced existing Web
Usage Mining method. Finally, explores the effectiveness of the
proposed approach than the existing Web Usage Mining by the
analysis of the experiments within the scope of web page
recommendations.