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- W3040340887 abstract "High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, where utility is used to measure the importance or weight of a sequence. However, the underlying informative knowledge of hierarchical relation between different items is ignored in HUSPM, which makes HUSPM unable to extract more interesting patterns. In this paper, we incorporate the hierarchical relation of items into HUSPM and propose a two-phase algorithm MHUH, the first algorithm for high-utility hierarchical sequential pattern mining (HUHSPM). In the first phase named Extension, we use the existing algorithm FHUSpan which we proposed earlier to efficiently mine the general high-utility sequences (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mi>g</mml:mi></mml:math>-sequences); in the second phase named Replacement, we mine the special high-utility sequences with the hierarchical relation (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mi>s</mml:mi></mml:math>-sequences) as high-utility hierarchical sequential patterns from <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mi>g</mml:mi></mml:math>-sequences. For further improvements of efficiency, MHUH takes several strategies such as Reduction, FGS, and PBS and a novel upper bounder TSWU, which will be able to greatly reduce the search space. Substantial experiments were conducted on both real and synthetic datasets to assess the performance of the two-phase algorithm MHUH in terms of runtime, number of patterns, and scalability. Conclusion can be drawn from the experiment that MHUH extracts more interesting patterns with underlying informative knowledge efficiently in HUHSPM." @default.
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- W3040340887 date "2020-07-06" @default.
- W3040340887 modified "2023-10-17" @default.
- W3040340887 title "An Efficient Algorithm for Extracting High-Utility Hierarchical Sequential Patterns" @default.
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- W3040340887 doi "https://doi.org/10.1155/2020/8816228" @default.
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