Ida Mele
ABSTRACT
Web usage mining is the application of data mining techniques to the data generated by the interactions of users with web servers. This kind of data, stored in server logs, represents a valuable source of information, which can be exploited to optimize the document-retrieval task, or to better understand, and thus, satisfy user needs.
Our research focuses on two important issues: improving search-engine performance through static caching of search results, and helping users to find interesting web pages by recommending news articles and blog posts.
Concerning the static caching of search results, we present the query covering approach. The general idea is to populate the cache with those documents that contribute to the result pages of a large number of queries, as opposed to caching the top documents of most frequent queries.
For the recommendation of web pages, we present a graph-based approach, which leverages the user-browsing logs to identify early adopters. These users discover interesting content before others, and monitoring their activity we can find web pages to recommend.
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Index Terms
- Web usage mining for enhancing search-result delivery and helping users to find interesting web content
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