Incorporating seasonality into search suggestions derived from intranet query logs

Dignum, S., Kruschwitz, U., Fasli, M., Kim, Y. , Song, D., Beresi, U.C. and de Roeck, A. (2010) Incorporating seasonality into search suggestions derived from intranet query logs. In: 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Toronto, Canada, 31 Aug - 3 Sept 2010, pp. 425-430. (doi: 10.1109/WI-IAT.2010.258)

Abstract

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 Proceedings
• Keywords: Information retrieval, interactive search, intranet search, local Web search, adaptive domain models, ant colony optimisation
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Kim, Dr Yunhyong
• Authors: Dignum, S., Kruschwitz, U., Fasli, M., Kim, Y., Song, D., Beresi, U.C., and de Roeck, A.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science; Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
• College/School: College of Arts & Humanities > School of Humanities > Information Studies
• Publisher: IEEE Computer Society