Collaborative and Usage-Driven Evolution of Personal Ontologies

Abstract

Abstract. Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogenous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. Of particular interest for supporting users during the personalization are collaborative filtering systems which can produce personal recommendations by computing the similarity between own preferences and the one of other people. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.

A survey of Web clustering engines

“…This can be seen as another form of personalized (adaptive) clustering. The proposed techniques exploit user feedback, whether explicit or implicit (e.g., clickthrough data), to filter out parts of the hierarchy that are presumably of no interest to the user Ferragina and Gulli [2005], Haase et al [2005]; Pierrakos and Paliouras [2005].…”

Supporting collaborative hierarchical classification: Bookmarks as an example

“…This collaborative methodology of recommending structural information has scarcely been researched in the context of hierarchical classification schemes. Haase et al [7] presented a more general approach of how the evolution and management of personal ontologies can be supported by a collaborative recommendation algorithm.…”

Evaluation of Ontology Enhancement Tools

“…A method for the generation and evaluation of suggestions towards an ontology user is proposed in [5]. The authors propose a recommendation engine that explores the activities of multiple users, who expand their personal ontologies from a shared basic ontology and suggest metrics for the evaluation of the engine's suggestions.…”