This paper presents Prospector, an adaptive meta-search layer, which performs personalized re-ordering of search results. Prospector combines elements from two approaches to adaptive search support: (a) collaborative web searching; and, (b) personalized searching using semantic metadata. The paper focuses on the way semantic metadata and the users' search behavior are utilized for user- and group- modeling, as well as on how these models are used to re-rank results returned for individual queries. The paper also outlines past evaluation activities related to Prospector, and discusses potential applications of the approach for the adaptive retrieval of multimedia documents. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Paramythis, A., König, F., Schwendtner, C., & Van Velsen, L. (2010). Using thematic ontologies for user- and group-based adaptive personalization in web searching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5811 LNCS, pp. 18–27). https://doi.org/10.1007/978-3-642-14758-6_2
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