關鍵字查詢 | 類別:期刊論文 | | 關鍵字:Discover Sequential Patterns in Incremental Database

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序號 學年期 教師動態
1 96/1 軍訓室 張忠義 少校教官 期刊論文 發佈 Discover Sequential Patterns in Incremental Database , [96-1] :Discover Sequential Patterns in Incremental Database期刊論文Discover Sequential Patterns in Incremental DatabaseLin, Nancy P.; Hao, Wei Hua; Chen, Hung Jen; Chueh, Hao En; Chang, Chung I淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 4(1), pp.197-201The task of sequential pattern mining is to discover the complete set of sequential patterns in a given sequence database with minimum support threshold. But in practice, minimum support some time is defined afterward, or need to be adjusted to discover information that interest to knowledge workers. In the same time, the problem of discover sequential patterns in a incremental database is an essential issue in real world practice of datamining. This paper discusses the issue of maintaining discovered sequential patterns when some information is appended to a sequence database. Many previous works based on Apriori-like approaches are not capable to do so without re-running previously presented algorithms o
2 96/1 資工系 闕豪恩 助理教授 期刊論文 發佈 Discover Sequential Patterns in Incremental Database , [96-1] :Discover Sequential Patterns in Incremental Database期刊論文Discover Sequential Patterns in Incremental DatabaseLin, Nancy P.; Hao, Wei Hua; Chen, Hung Jen; Chueh, Hao En; Chang, Chung I淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 4(1), pp.197-201The task of sequential pattern mining is to discover the complete set of sequential patterns in a given sequence database with minimum support threshold. But in practice, minimum support some time is defined afterward, or need to be adjusted to discover information that interest to knowledge workers. In the same time, the problem of discover sequential patterns in a incremental database is an essential issue in real world practice of datamining. This paper discusses the issue of maintaining discovered sequential patterns when some information is appended to a sequence database. Many previous works based on Apriori-like approaches are not capable to do so without re-running previously presented algorithms o
3 96/1 資工系 陳宏任 講師 期刊論文 發佈 Discover Sequential Patterns in Incremental Database , [96-1] :Discover Sequential Patterns in Incremental Database期刊論文Discover Sequential Patterns in Incremental DatabaseLin, Nancy P.; Hao, Wei Hua; Chen, Hung Jen; Chueh, Hao En; Chang, Chung I淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 4(1), pp.197-201The task of sequential pattern mining is to discover the complete set of sequential patterns in a given sequence database with minimum support threshold. But in practice, minimum support some time is defined afterward, or need to be adjusted to discover information that interest to knowledge workers. In the same time, the problem of discover sequential patterns in a incremental database is an essential issue in real world practice of datamining. This paper discusses the issue of maintaining discovered sequential patterns when some information is appended to a sequence database. Many previous works based on Apriori-like approaches are not capable to do so without re-running previously presented algorithms o
4 96/1 資工系 郝維華 講師 期刊論文 發佈 Discover Sequential Patterns in Incremental Database , [96-1] :Discover Sequential Patterns in Incremental Database期刊論文Discover Sequential Patterns in Incremental DatabaseLin, Nancy P.; Hao, Wei Hua; Chen, Hung Jen; Chueh, Hao En; Chang, Chung I淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 4(1), pp.197-201The task of sequential pattern mining is to discover the complete set of sequential patterns in a given sequence database with minimum support threshold. But in practice, minimum support some time is defined afterward, or need to be adjusted to discover information that interest to knowledge workers. In the same time, the problem of discover sequential patterns in a incremental database is an essential issue in real world practice of datamining. This paper discusses the issue of maintaining discovered sequential patterns when some information is appended to a sequence database. Many previous works based on Apriori-like approaches are not capable to do so without re-running previously presented algorithms o
5 96/1 資工系 林丕靜 副教授 期刊論文 發佈 Discover Sequential Patterns in Incremental Database , [96-1] :Discover Sequential Patterns in Incremental Database期刊論文Discover Sequential Patterns in Incremental DatabaseLin, Nancy P.; Hao, Wei Hua; Chen, Hung Jen; Chueh, Hao En; Chang, Chung I淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 4(1), pp.197-201The task of sequential pattern mining is to discover the complete set of sequential patterns in a given sequence database with minimum support threshold. But in practice, minimum support some time is defined afterward, or need to be adjusted to discover information that interest to knowledge workers. In the same time, the problem of discover sequential patterns in a incremental database is an essential issue in real world practice of datamining. This paper discusses the issue of maintaining discovered sequential patterns when some information is appended to a sequence database. Many previous works based on Apriori-like approaches are not capable to do so without re-running previously presented algorithms o
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