Abstract
During the online shopping process, users search for interesting products in order to quickly access those that fit with their needs among a long tail of similar or closely related products. Our contribution addresses head queries that are frequently submitted on e-commerce Web sites. Head queries usually target featured products with several variations, accessories, and complementary products. We present in this paper a product feature-based user-centric model for product search involving, in addition to product characteristics, the user engagement toward the product. This model has been evaluated through the product search track of the LL4IR lab at CLEF 2015 in order to highlight the effectiveness of our model as well as the impact of the user engagement factor.
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CITATION STYLE
Jabeur, L. B., Soulier, L., Tamine, L., & Mousset, P. (2016). A product feature-based user-centric ranking model for E-commerce search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9822 LNCS, pp. 174–186). Springer Verlag. https://doi.org/10.1007/978-3-319-44564-9_14
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