Kruschwitz, Udo and Lungley, Deirdre and Albakour, M‐Dyaa and Song, Dawei (2013) Deriving query suggestions for site search. Journal of the American Society for Information Science and Technology, 64 (10). pp. 1975-1994. DOI https://doi.org/10.1002/asi.22901
Kruschwitz, Udo and Lungley, Deirdre and Albakour, M‐Dyaa and Song, Dawei (2013) Deriving query suggestions for site search. Journal of the American Society for Information Science and Technology, 64 (10). pp. 1975-1994. DOI https://doi.org/10.1002/asi.22901
Kruschwitz, Udo and Lungley, Deirdre and Albakour, M‐Dyaa and Song, Dawei (2013) Deriving query suggestions for site search. Journal of the American Society for Information Science and Technology, 64 (10). pp. 1975-1994. DOI https://doi.org/10.1002/asi.22901
Abstract
<jats:p>Modern search engines have been moving away from simplistic interfaces that aimed at satisfying a user's need with a single‐shot query. Interactive features are now integral parts of web search engines. However, generating good query modification suggestions remains a challenging issue. Query log analysis is one of the major strands of work in this direction. Although much research has been performed on query logs collected on the web as a whole, query log analysis to enhance search on smaller and more focused collections has attracted less attention, despite its increasing practical importance. In this article, we report on a systematic study of different query modification methods applied to a substantial query log collected on a local website that already uses an interactive search engine. We conducted experiments in which we asked users to assess the relevance of potential query modification suggestions that have been constructed using a range of log analysis methods and different baseline approaches. The experimental results demonstrate the usefulness of log analysis to extract query modification suggestions. Furthermore, our experiments demonstrate that a more fine‐grained approach than grouping search requests into sessions allows for extraction of better refinement terms from query log files.</jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | search engines; domain knowledge; search terms |
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: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 06 Aug 2013 08:47 |
Last Modified: | 30 Oct 2024 19:56 |
URI: | http://repository.essex.ac.uk/id/eprint/7248 |
Available files
Filename: kruschwitz_jasist2012_preprint.pdf