關鍵字查詢 | 類別:期刊論文 | | 關鍵字:Fast Mining of Closed Sequential Patterns

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序號 學年期 教師動態
1 96/2 軍訓室 張忠義 少校教官 期刊論文 發佈 Fast Mining of Closed Sequential Patterns , [96-2] :Fast Mining of Closed Sequential Patterns期刊論文Fast Mining of Closed Sequential PatternsLin, Nancy P.; Hao, Wei-hua; Chen, Hung-jen; Chueh, Hao-en; Chang, Chung-i淡江大學軍訓室data mining;sequential patterns mining;closed sequential patternsAthens: World Scientific and Engineering Academy and SocietyWSEAS Transactions on Computers 7(4), pp.133-139This paper propose a novel algorithm for mining closed frequent sequences, a scalable, condensed and lossless structure of complete frequent sequences that can be mined from a sequence database. This algorithm, FMCSP, has applied several optimization methods, such as equivalence class, to alleviate the needs of searching space and run time. In particular, since one of the main issues in this type of algorithms is the redundant generation of the closed sequences, hence, we propose an effective and memory saving methods, different from previous works, does not require the complete set of closed sequences to be residing in the memory.20130327 已補正 by 游筑翔@@
2 96/2 資工系 闕豪恩 助理教授 期刊論文 發佈 Fast Mining of Closed Sequential Patterns , [96-2] :Fast Mining of Closed Sequential Patterns期刊論文Fast Mining of Closed Sequential PatternsLin, Nancy P.; Hao, Wei-hua; Chen, Hung-jen; Chueh, Hao-en; Chang, Chung-i淡江大學軍訓室data mining;sequential patterns mining;closed sequential patternsAthens: World Scientific and Engineering Academy and SocietyWSEAS Transactions on Computers 7(4), pp.133-139This paper propose a novel algorithm for mining closed frequent sequences, a scalable, condensed and lossless structure of complete frequent sequences that can be mined from a sequence database. This algorithm, FMCSP, has applied several optimization methods, such as equivalence class, to alleviate the needs of searching space and run time. In particular, since one of the main issues in this type of algorithms is the redundant generation of the closed sequences, hence, we propose an effective and memory saving methods, different from previous works, does not require the complete set of closed sequences to be residing in the memory.20130327 已補正 by 游筑翔@@
3 96/2 資工系 陳宏任 講師 期刊論文 發佈 Fast Mining of Closed Sequential Patterns , [96-2] :Fast Mining of Closed Sequential Patterns期刊論文Fast Mining of Closed Sequential PatternsLin, Nancy P.; Hao, Wei-hua; Chen, Hung-jen; Chueh, Hao-en; Chang, Chung-i淡江大學軍訓室data mining;sequential patterns mining;closed sequential patternsAthens: World Scientific and Engineering Academy and SocietyWSEAS Transactions on Computers 7(4), pp.133-139This paper propose a novel algorithm for mining closed frequent sequences, a scalable, condensed and lossless structure of complete frequent sequences that can be mined from a sequence database. This algorithm, FMCSP, has applied several optimization methods, such as equivalence class, to alleviate the needs of searching space and run time. In particular, since one of the main issues in this type of algorithms is the redundant generation of the closed sequences, hence, we propose an effective and memory saving methods, different from previous works, does not require the complete set of closed sequences to be residing in the memory.20130327 已補正 by 游筑翔@@
4 96/2 資工系 郝維華 講師 期刊論文 發佈 Fast Mining of Closed Sequential Patterns , [96-2] :Fast Mining of Closed Sequential Patterns期刊論文Fast Mining of Closed Sequential PatternsLin, Nancy P.; Hao, Wei-hua; Chen, Hung-jen; Chueh, Hao-en; Chang, Chung-i淡江大學軍訓室data mining;sequential patterns mining;closed sequential patternsAthens: World Scientific and Engineering Academy and SocietyWSEAS Transactions on Computers 7(4), pp.133-139This paper propose a novel algorithm for mining closed frequent sequences, a scalable, condensed and lossless structure of complete frequent sequences that can be mined from a sequence database. This algorithm, FMCSP, has applied several optimization methods, such as equivalence class, to alleviate the needs of searching space and run time. In particular, since one of the main issues in this type of algorithms is the redundant generation of the closed sequences, hence, we propose an effective and memory saving methods, different from previous works, does not require the complete set of closed sequences to be residing in the memory.20130327 已補正 by 游筑翔@@
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