Abstract
We present a method to help a user redefine a query based on past users experience, namely the click-through data as recorded by a search engine. Unlike most previous works, the method we propose attempts to recommend better queries rather than related queries. It is effective at identifying query specialization or sub-topics because it take into account the co-occurrence of documents in individual query sessions. It is also particularly simple to implement.
This research was supported by Millennium Nucleus, Center for Web Research (P04-067-F), Mideplan, Chile.
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Dupret, G., Mendoza, M. (2005). Recommending Better Queries from Click-Through Data. In: Consens, M., Navarro, G. (eds) String Processing and Information Retrieval. SPIRE 2005. Lecture Notes in Computer Science, vol 3772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575832_5
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DOI: https://doi.org/10.1007/11575832_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29740-6
Online ISBN: 978-3-540-32241-2
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