Faceted browsing is widely used in Web shops and product comparison sites. In these cases, a fixed ordered list of facets is often employed. This approach suffers from two main issues. First, one needs to invest a significant amount of time to devise an effective list. Second, with a fixed list of facets, it can happen that a facet becomes useless if all products that match the query are associated to that particular facet. In this work, we present a framework for dynamic facet ordering in e-commerce. Based on measures for specificity and dispersion of facet values, the fully automated algorithm ranks those properties and facets on top that lead to a quick drill-down for any possible target product. In contrast to existing solutions, the framework addresses e-commerce specific aspects, such as the possibility of multiple clicks, the grouping of facets by their corresponding properties, and the abundance of numeric facets. In a large-scale simulation and user study, our approach was, in general, favorably compared to a facet list created by domain experts, a greedy approach as baseline, and a state-of-the-art entropy-based solution.

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doi.org/10.1109/TKDE.2017.2652461, hdl.handle.net/1765/99640
ERIM Top-Core Articles
I E E E Transactions on Knowledge & Data Engineering
Erasmus School of Economics

Vandic, D., Aanen, S., Frasincar, F., & Kaymak, U. (2017). Dynamic Facet Ordering for Faceted Product Search Engines. I E E E Transactions on Knowledge & Data Engineering, 29(5), 1004–1016. doi:10.1109/TKDE.2017.2652461