First, sequences are clustered by similarity. Then, consensus patterns are mined directly from each cluster through multiple alignment.
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[PDF] Mining Integrated Sequential Patterns From Multiple Databases
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The International Journal of Data Warehousing and Mining is indexed or listed in the following: ABI/Inform; ACM. Digital Library; Australian Business Deans ...
Sequential pattern mining is used to find frequent data sequences over time. When sequential patterns are generated, the newly arriving patterns may not be ...
each branch. Each branch can mine its local data for local decision making using traditional mining technology. Naturally, these local patterns can then be ...
In this chapter we first introduce sequence data. We then discuss different approaches for mining of patterns from sequence data, studied in literature.
Mar 31, 2021 · It supports constraint-based frequent sequential pattern mining. Here is an example that shows how to mine a sequence database while respecting ...
Apr 20, 2006 · We propose the theme of approximate sequential pattern mining roughly defined as identifying patterns approximately shared by many sequences.
Sequential pattern mining is a special case of structured data mining. There are several key traditional computational problems addressed within this field.
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Sequential pattern mining in multi-databases via multiple alignment. In DMKD, 12(2-3), pp. 151-180, 2006. 4. H.C. Kum, J.H. Chang, and W. Wang. Benchmarking ...
We present a novel algorithm, ApproxMAP, to mine approximate sequential patterns, called consensus patterns, from large sequence databases in two steps. First, ...