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基于廣義后綴樹的事件序列頻繁情節挖掘算法

Mining algorithm of frequent episodes in an event sequence based on generalized suffix-tree

  • 摘要: 為了有效地挖掘事件序列頻繁情節,提出了一種廣義后綴樹結構發現和存儲頻繁情節.此結構利用廣義后綴概念并且樹中只包含頻繁情節結點,用頻繁情節發生列表逐層構建的方法提高了建樹效率.該方法充分利用了事件序列的有序特點,可用于發現各類頻繁情節.實驗結果表明該算法性能優于Apriori-like頻繁情節發現算法.

     

    Abstract: In order to mine frequent episodes from an event sequence efficiently, an algorithm based on generalized suffix-tree was proposed to discover and store frequent episodes, which uses the concept of generalized suffix and contains only frequent episodes' nodes. The occurrence list of frequent episodes was used layer-upon-layer to improve the efficiency of the tree. The algorithm make full use of the order character of an event sequence and may discover the variety of frequent episodes. Experimental results show that the proposed algorithm is superior in runtime to Apriori-like frequent episodes mining algorithm.

     

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