Showing papers by "Magdalini Eirinaki published in 2004"

Web personalization integrating content semantics and navigational patterns

Abstract: The amounts of information residing on web sites make users' navigation a hard task. To address this problem, web sites provide recommendations to the end users, based on similar users' navigational patterns mined from past visits. In this paper we introduce a recommendation method, which integrates usage data recorded in web logs, and the conceptual relationships between web documents. In the proposed framework, the usage-oriented URI representation of web pages and users' behavior is augmented with content-based semantics expressed using domain-ontology terms. Since the number of multilingual web sites is constantly increasing, we also propose an automatic method for uniformly characterizing a web site's documents using a common vocabulary. Both methods are integrated in the semantic web personalization system SEWeP.

Archiving the Greek Web

Abstract: Web sites have become an increasingly important part of every country’s information and cultural heritage. For this reason, Web archiving has become an issue for many national libraries. In this paper, we present a first attempt to archive the Greek Web. This project is divided in two parts; the first part concerns the collection of the majority of Greek Web pages. The second part focuses on the knowledge extraction from this archive, in order to classify it in semantically coherent clusters. Considerations concerning the criteria that should be set in order to characterize a Web page as “Greek” are discussed. A combination of IR and content mining techniques is applied in order to semantically characterize the collected content. We especially address the bilingualism issue arising because the content is written in both Greek and English. The collected Web pages are finally classified into meaningful clusters, facilitating the searching of the archive.

SEWeP: a web mining system supporting semantic personalization

Abstract: We present SEWeP, a Web Personalization prototype system that integrates usage data with content semantics, expressed in taxonomy terms, in order to produce a broader yet semantically focused set of recommendations.