Abstract
In this paper, a method is proposed to dynamically construct a faceted interface to help users navigate web search results for finding required data efficiently. The proposed method consists of two processing steps: 1) candidate facets extraction, and 2) facet hierarchy construction. At first, the category information of entities in Wikipedia and a learning model are used to select the query-dependent facet terms for constructing the facet hierarchy. Then an objective function is designed to estimate the average browsing cost of users when accessing the search results by a given facet hierarchy. Accordingly, two greedy based algorithms, one is a bottom-up approach and another one is a top-down approach, are proposed to construct a facet hierarchy for optimizing the objective function. A systematic performance study is performed to verify the effectiveness and the efficiency of the proposed algorithms.
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Chang, W., Koh, JL. (2015). Dynamic Facet Hierarchy Constructing for Browsing Web Search Results Efficiently. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_29
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DOI: https://doi.org/10.1007/978-3-319-19066-2_29
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