Research Repository

Incorporating Seasonality into Search Suggestions Derived from Intranet Query Logs

Dignum, Stephen and Kruschwitz, Udo and Fasli, Maria and Kim, Yunhyong and Song, Dawei and Beresi, Ulises Cervino and de Roeck, Anne (2010) Incorporating Seasonality into Search Suggestions Derived from Intranet Query Logs. In: 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT), 2010-08-31 - 2010-09-03.

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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. © 2010 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 14 Aug 2012 14:45
Last Modified: 15 Jan 2022 00:37

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