Τίτλος:
Exploiting probabilistic latent information for the construction of Community Web Directories
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
This paper improves a recently-presented approach to Web Personalization, named Community Web Directories, which applies personalization techniques to Web Directories. The Web directory is viewed as a concept hierarchy and personalization is realized by constructing user community models on the basis of usage data collected by the proxy servers of an Internet Service Provider. The user communities are modeled using Probabilistic Latent Semantic Analysis (PLSA), which provides a number of advantages such as overlapping communities, as well as a good rationale for the associations that exist in the data. The data that are analyzed present challenging peculiarities such as their large volume and semantic diversity. Initial results presented in this paper illustrate the effectiveness of the new method. © Springer-Verlag Berlin Heidelberg 2005.
Συγγραφείς:
Pierrakos, D.
Paliouras, G.
Περιοδικό:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Λέξεις-κλειδιά:
Computer science; Data acquisition; Internet; Probability; Semantics; Servers, Internet Service Provider; Probabilistic Latent Semantic Analysis (PLSA); Semantic diversity; Web directory, World Wide Web
