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This document summarizes a research paper presented at the 2020 IEEE International Conference on Big Data about a novel weighted FP-Stream algorithm for analyzing IoT data streams. The paper proposes enhancements to the conventional FP-Stream algorithm to make it more adaptive to concept drifts while retaining applicability to data streams. Specifically, it adds weights during pattern pruning based on pattern freshness, prioritizing newer patterns and allowing older patterns to be forgotten more quickly. Th
- Author
- 戴积文
- Language
- EN