Hierarchical faceted metadata in site search interfaces
CHI '02 Extended Abstracts on Human Factors in Computing Systems
User Modeling and User-Adapted Interaction
Proceedings of the 16th international conference on World Wide Web
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Personalized interactive faceted search
Proceedings of the 17th international conference on World Wide Web
Backward highlighting: enhancing faceted search
Proceedings of the 21st annual ACM symposium on User interface software and technology
What do exploratory searchers look at in a faceted search interface?
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Dynamic Taxonomies and Faceted Search: Theory, Practice, and Experience
Dynamic Taxonomies and Faceted Search: Theory, Practice, and Experience
Information Processing and Management: an International Journal
Faceted Search
Approximately optimal facet selection
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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Multifaceted search is a commonly used interaction paradigm in e-commerce applications, such as Web shops. Because of the large amount of possible product attributes, Web shops usually make use of static information to determine which facets should be displayed. Unfortunately, this approach does not take into account the user query, leading to a non-optimal facet drill down process. In this paper, we focus on automatic facet selection, with the goal of minimizing the number of steps needed to find the desired product. We propose several algorithms for facet selection, which we evaluate against the state-of-the-art algorithms from the literature. We implement our approach in a Web application called faccy.net. The evaluation is based on simulations employing 1000 queries, 980 products, 487 facets, and three drill down strategies. As evaluation metrics we use the average number of clicks, the average utility, and the top-10 promotion percentage. The results show that the Probabilistic Entropy algorithm significantly outperforms the other considered algorithms.