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Incorporating seasonality into search suggestions derived from intranet query logs

Dignum, Stephen; Kruschwitz, Udo; Fasli, Maria; Kim, Yunhyong; Song, Dawei; Cerviño Beresi, Ulises and De Roeck, Anne (2010). Incorporating seasonality into search suggestions derived from intranet query logs. In: IEEE/WIC/ACM International Conference on Web Intelligence (WI2010), 31 Aug 31-3 Sep 2010, Toronto, Canada.

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While much research has been performed on query logs collected for major Web search engines, query log analysis to enhance search on smaller and more focused collections has attracted less attention. Our hypothesis is that an intranet search engine can be enhanced by adapting the search system to real users’ search behaviour through exploiting its query logs. In this work we describe how a constantly adapting domain model can be used to identify and capture changes in intranet users’ search requirements over time. We employ an algorithm that dynamically builds a domain model from query modifications taken from an intranet query log and employs a decay measure, as used in Machine Learning and Optimisation methods, to promote more recent terms. This model is used to suggest query refinements and additions to users and to elevate seasonally relevant terms. A user evaluation using models constructed from a substantial university intranet query log is provided. Statistical evidence demonstrates the system’s ability to suggest seasonally relevant terms over three different academic trimesters. We conclude that log files of an intranet search engine are a rich resource to build adaptive domain models, and in our experiments these models significantly outperform sensible baselines.

Item Type: Conference or Workshop Item
Copyright Holders: 2010 IEEE
Keywords: information retrieval; interactive search; intranet search; local Web search; adaptive domain models; ant colony optimisation
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: 35138
Depositing User: Dawei Song
Date Deposited: 01 Nov 2012 12:09
Last Modified: 07 Dec 2018 17:10
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