Abstract
Processing information in web pages and navigation on the web can take significant amount of time for users, requiring them to employ higher cognitive processes such as generalization and categorization. Providing users with annotated entities and terms contained in the text, and adaptive navigation based on these terms could help with the comprehension and better their orientation in the information space. In this paper, we present a method for ad-hoc navigation based on automatic terms retrieval, ranking and categorization. Recognized terms and categories are used as keywords for search in available content offering information spaces. Retrieved hyperlinks can be browsed by the user, while terms and categories gained from the last analyzed page are still available. Finally, the method includes user profiling, which enables grouping of the users based on their preferred terms and categories. Our results show that ad-hoc navigation can ease access to relevant related content on the web.
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Ševce, O., Tvarožek, J., Bieliková, M. (2010). Term Ranking and Categorization for Ad-Hoc Navigation. In: Dicheva, D., Dochev, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2010. Lecture Notes in Computer Science(), vol 6304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15431-7_8
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DOI: https://doi.org/10.1007/978-3-642-15431-7_8
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