We propose a time windowing technique for the incremental maintenance of association rules, which can focus on finding strong association rules within current data and avoid the use of outdated data.

笔者提出一种用于增量式关联规则维护的时间窗口技术。该技术可以集中在当前数据中发现强关联规则，避免利用过时数据。

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But the recently developed "thermal windowing" technique of TSC avoids this process by considering complicated temperature change and the time relaxation process in the measurement.

而基于“温度窗口”的热刺激电流技术因考虑速冷极化过程涉及复杂的温度变化和时间弛豫过程，排除了这一过程。

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