Increasing the authoritativeness of web recommendations using PageRank‐based approaches

Web content has been widely used for recommending personal webpages. Despite its popularity, the content‐based approach regards a webpage simply as a piece of text, thereby often resulting in less authoritative recommendations of webpages. This paper aims to propose novel approaches that utilise other sources of information pertaining to webpages to facilitate the automatic construction of an authoritative web recommender system.

In this research, four approaches that exploit hyperlink structure, web content and web‐usage logs for making recommendations are proposed. The proposed approaches have been implemented as a prototype system, called the authoritative web recommender (AWR) system. An evaluation using the web‐usage logs and the corresponding pages of a university web site was performed.

The results from the evaluations using empirical data demonstrate that the four proposed approaches outperform the traditional content‐only approach.

This paper describes a novel way to combine information retrieval, usage mining and hyperlink structure analysis techniques to find relevant and authoritative webpages for recommendation.