Abstract
This paper proposes a compositional framework for discovering interesting range information from huge databases, where a domain specific query language is provided to specify the range of interest, and a general algorithm is given to mine the range specified in this language efficiently. A wide class of longest range problems, including the intensively studied optimized support range problem [FMMT96], can be solved systematically in this framework. Experiments with real world databases show that our framework is efficient not only in theory but also in practice.
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Zhao, H., Hu, Z., Takeichi, M. (2002). A Compositional Framework for Mining Longest Ranges. In: Lange, S., Satoh, K., Smith, C.H. (eds) Discovery Science. DS 2002. Lecture Notes in Computer Science, vol 2534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36182-0_42
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DOI: https://doi.org/10.1007/3-540-36182-0_42
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