Multi-Select Faceted Navigation based on Minimum Description Length Principle
Chao He, Xueqi Cheng and Jiafeng Guo
Faceted navigation can effectively reduce user efforts of reaching targeted resources in databases, by suggesting dynamic facet values for iterative query refinement. A key issue is minimizing the navigation cost in a user query session. Conventional navigation scheme assumes that at each step, users select only one suggested value to figure out resources containing it. To make faceted navigation more flexible and effective, this paper introduces a multi-select scheme where multiple suggested values can be selected at one step, and a selected value can be used to either retain or exclude the resources containing it. Previous algorithms for cost-driven value suggestion cannot work well under our navigation scheme. Therefore, we propose to optimize the navigation cost using the Minimum Description Length principle, which can well balance the number of navigation steps and the number of suggested values per step under our new scheme. Empirical study demonstrates that our approach is more cost-saving and efficient than state-of-the-art approaches.