Abstract
In this paper we propose a query suggestion method for price comparison search engines. Query suggestion techniques are used for generating alternative queries to facilitate web users in information seeking; in this specific domain, suggestions provided to web users need to be properly generated taking into account that the suggested products must be still available for sale. We propose a novel approach based on a slightly variant of classical query-URL graphs: the query-product click-through bipartite graph. Information extracted both from search engine logs and specific domain features are exploited to build the graph, and one of the advantages of this model is that such a graph can be used to suggest not only related queries but also related products. Concepts used in the proposed method are not restricted to our context but are used in many other major e-commerce and search engine websites, we tested the model on several challenging datasets, and also compared with a recent query suggestion approach specifically designed for price comparison engines. Our solution outperforms the competing approach, achieving higher results in terms of relevance of the provided suggestions and coverage rates on top-8 suggestions.
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Noce, L., Gallo, I., Zamberletti, A., Calefati, A. (2017). A Query and Product Suggestion Method for Price Comparison Search Engines. In: Monfort, V., Krempels, KH., Majchrzak, T., Traverso, P. (eds) Web Information Systems and Technologies. WEBIST 2016. Lecture Notes in Business Information Processing, vol 292. Springer, Cham. https://doi.org/10.1007/978-3-319-66468-2_1
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DOI: https://doi.org/10.1007/978-3-319-66468-2_1
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