Abstract
There are numerous queries for which search engine results are not satisfactory. For instance, the user may submit an ambiguous or miss-spelled query; or there might be a mismatch between query and document vocabulary, or even character set in some languages. Different automatic methods for query rewriting / refinement have been proposed in the literature, but little work has been done on how to combine the results of these rewrites to find relevant documents. In this paper, we review some techniques efficient enough to be computed online and we discuss their respective assumptions. We also propose and discuss a new model that is theoretically more appealing while still computationally very efficient. Our experiments show that all methods manage to improve the ranking of a leading commercial search engine.
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Dupret, G., Zilleruelo-Ramos, R., Fujita, S. (2010). Using Related Queries to Improve Web Search Results Ranking. In: Chavez, E., Lonardi, S. (eds) String Processing and Information Retrieval. SPIRE 2010. Lecture Notes in Computer Science, vol 6393. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16321-0_22
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DOI: https://doi.org/10.1007/978-3-642-16321-0_22
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