Abstract
Search engine queries have evolved over the past 30 years from complex Boolean formulations to short lists of “keywords.” Despite the apparent simplicity of short queries, choosing the right keywords can be difficult, and understanding user intentions is a major challenge. Techniques such as query expansion and context-based profiles have been developed to address these problems, but with limited success. Rather than trying to infer user intentions from very short queries, another approach is to improve query processing and retrieval models for long queries. In particular, query transformation is a new approach to improving search that appears to have considerable potential. In this approach, queries are transformed into one or more new queries using probabilistic models for generation or search of query archives. I will describe various transformation models and the role of a retrieval model in using these transformations. Examples will be given from applications such as collaborative question answering and forum search.
Chapter PDF
Similar content being viewed by others
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Croft, W.B. (2009). Query Evolution. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00958-7_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-00958-7_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00957-0
Online ISBN: 978-3-642-00958-7
eBook Packages: Computer ScienceComputer Science (R0)