Dynamic Facet Ordering for Faceted Product Search Engines (Extended Abstract)

Currently many webshops rely on a fixed list of product facets to help users find the products of interest. Such a solution suffers from two problems: (1) it is difficult to devise a fixed list of facets that would satisfy all user interests, and (2) the top facets could become obsolete when all product results have these facets. To address these two problems we propose a novel algorithm for dynamic ordering of the product facets based on the query results. This algorithm relies on measures such as specificity and dispersion for qualitative and quantitative facets, respectively, to rank the properties associated with these facets so that users are able to find the products of interest with a minimum number of drill-down steps. Using a large-scale simulation study and a user-based evaluation, we show that our algorithm outperforms the expert-based fixed facets approach, a greedy baseline, and a state-of-the-art entropy-based solution. This paper is an extended abstract of our previous work [1].