Albakour, M-Dyaa; Kruschwitz, Udo; Song, Dawei; Fasli, Maria and De Roeck, Anne
(2011).
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-642-25631-8_18 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
The increased availability of large amounts of data about user search behaviour in search engines has triggered a lot of research in recent years. This includes developing machine learning methods to build knowledge structures that could be exploited for a number of tasks such as query recommendation. Query flow graphs are a successful example of these structures, they are generated from the sequence of queries typed in by a user in a search session. In this paper we propose to modify the query flow graph by incorporating clickthrough information from the search logs. Click information provides evidence of the success or failure of the search journey and therefore can be used to enrich the query flow graph to make it more accurate and useful for query recommendation. We propose a method of adjusting the weights on the edges of the query flow graph by incorporating the number of clicked documents after submitting a query.
We explore a number of weighting functions for the graph edges using click information. Applying an automated evaluation framework to assess query recommendations allows us to perform automatic and reproducible evaluation experiments. We demonstrate how our modified query flow graph outperforms the standard query flow graph. The experiments are conducted on the search logs of an academic organisation’s search engine and validated in a second experiment on the log files of another Web site.
| Item Type: | Conference Item |
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| Copyright Holders: | 2011 Springer |
| Extra Information: | Published in Proceedings AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology, Pages 193-204, Springer-Verlag, ISBN: 978-3-642-25630-1. |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Mathematics, Computing and Technology |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 34685 |
| Depositing User: | Dawei Song |
| Date Deposited: | 16 Oct 2012 09:49 |
| Last Modified: | 23 Oct 2012 16:02 |
| URI: | http://oro.open.ac.uk/id/eprint/34685 |
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