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Exploiting click logs for adaptive intranet navigation

Saad, SZ and Kruschwitz, U (2013) Exploiting click logs for adaptive intranet navigation. In: UNSPECIFIED, ? - ?.

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Web sites and intranets can be difficult to navigate as they tend to be rather static and a new user might have no idea what documents are most relevant to his or her need. Our aim is to capture the navigational behaviour of existing users (as recorded in the click logs) so that we can assist future users by proposing the most relevant pages as they navigate the site without changing the actual Web site and do this adaptively so that a continuous learning cycle is being employed. In this paper we explore three different algorithms that can be employed to learn such suggestions from navigation logs. We find that users managed to conduct the tasks significantly quicker than the (purely frequency-based) baseline by employing ant colony optimisation or random walk approaches to the log data for building a suggestion model. © 2013 Springer-Verlag.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 27 Jul 2017 13:29
Last Modified: 17 Aug 2017 17:33

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