Incorporating Seasonality into Search Suggestions Derived from Intranet Query Logs

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 evidenc...

• Type: Journal
• Year: 2010
• Where: WEBI
• Authors: Stephen Dignum, Udo Kruschwitz, Maria Fasli, Yunhyong Kim, Dawei Song, Ulises Cerviño Beresi, Anne N. De Roeck
• Keywords: Domain Models, Internet Technology, Query Log, Search Engine, WEBI 2010