Abstract
This paper proposes a subtopic mining method based on three-level hierarchical search intentions. Various subtopic candidates are extracted from web documents using a simple pattern, and higher-level and lower-level subtopics are selected from these candidates. The selected subtopics as second-level subtopics are ranked by a proposed measure, and are expanded and re-ranked considering the characteristics of resources. Using general terms in the higher-level subtopics, we make second-level subtopic groups and generate first-level subtopics. Our method achieved better performance than a state of the art method.
This work was partly supported by the ICT R&D program of MSIP/IITP (10041807), the SYSTRAN International corporation, the BK 21+ Project, and the National Korea Science and Engineering Foundation (KOSEF) (NRF-2010-0012662).
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Notes
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Query dimensions are groups of items extracted from the style of lists such as tables in top retrieved documents [6]. Each dimension has a ranked list of its items.
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Kim, SJ., Shin, J., Lee, JH. (2016). Subtopic Mining Based on Three-Level Hierarchical Search Intentions. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_62
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DOI: https://doi.org/10.1007/978-3-319-30671-1_62
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