The problem Autodesk sees is the growing amount of data in organizations and growing complexity in workflow and process management.

Autodesk看到的问题是组织中日益增加的数据量和日趋复杂的工作流和管理流程。

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This paper proposes an algorithm of Mining Frequent closed itemsets with Window Sliding Rapidly(MFWSR) against the complexity of data structure and process for determination.

针对频繁闭项集挖掘算法中数据结构与处理机制复杂的问题，提出窗口快速滑动的数据流频繁闭项集挖掘算法——MFWSR。

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Experiments on chunking recognition and Part-of-Speech tagging are conducted to show that the new data structure greatly speeds up the feature matching process while keeping the same space complexity.

基本短语识别和词性标注的实验显示，这种新的数据结构的确能够极大地加快最大熵方法执行系统的速度，同时保持空间复杂度不变。

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