Improving semantic search via integrated personalized faceted and visual graph navigation

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Abstract

Growing need for information retrieval, information processing, and the associated need for navigation in existing information spaces resulted in several approaches that aim to improve efficiency of the respective user tasks. However, problems related to user navigation and orientation in large open information spaces still persist possibly due to increasing demands and the imperfections of individual approaches. We propose an integrated search and navigation solution that takes advantage of the faceted browsing paradigm and visual navigation in graphs both extended with support for automatic personalization based on user context also taking advantage of a user's social network. The proposed solution is primarily evaluated in the domain of scientific publications, i.e. digital libraries, with possible extensions to other application domains. © Springer-Verlag Berlin Heidelberg 2008.

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Tvarožek, M., Barla, M., Frivolt, G., Tomša, M., & Bieliková, M. (2008). Improving semantic search via integrated personalized faceted and visual graph navigation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4910 LNCS, pp. 778–789). https://doi.org/10.1007/978-3-540-77566-9_67

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