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Exploring ant colony optimisation for adaptive interactive search

Albakour, M-Dyaa; Kruschwitz, Udo; Nanas, Nikolaos; Song, Dawei; Fasli, Maria and De Roeck, Anne (2011). Exploring ant colony optimisation for adaptive interactive search. In: Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, 12-14 Sep 2011, Bertinoro, Italy, pp. 213–224.

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Search engines have become much more interactive in recent years which has triggered a lot of work in automatically acquiring knowledge structures that can assist a user in navigating through a document collection. Query log analysis has emerged as one of the most promising research areas to automatically derive such structures. We explore a biologically inspired model based on ant colony optimisation applied to query logs as an adaptive learning process that addresses the problem of deriving query suggestions. A user interaction with the search engine is treated as an individual ant’s journey and over time the collective journeys of all ants result in strengthening more popular paths which leads to a corresponding term association graph that is used to provide query modification suggestions. This association graph is being updated in a continuous learning cycle. In this paper we use a novel automatic evaluation framework based on actual query logs to explore the effect of different parameters in the ant colony optimisation algorithm on the performance of the resulting adaptive query suggestion model. We also use the framework to compare the ant colony approach against a state-of-the-art baseline. The experiments were conducted with query logs collected on a university search engine over a period of several years.

Item Type: Conference or Workshop Item
Copyright Holders: 2011 Springer-Verlag
Extra Information: Published in: G. Amati and F. Crestani (Eds.): ICTIR 2011, LNCS 6931, pp. 213–224, 2011.
Keywords: ant colony; interactive information retrieval; adaptive search
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 33106
Depositing User: Anne De Roeck
Date Deposited: 06 Mar 2012 16:33
Last Modified: 07 Dec 2018 23:10
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