{"title":"维护使用预大序列进行记录修改的顺序模式","authors":"Ching-Yao Wang, T. Hong, S. Tseng","doi":"10.1109/ICDM.2002.1184031","DOIUrl":null,"url":null,"abstract":"In previous work we proposed incremental mining algorithms for maintenance of sequential patterns based on the concept of pre-large sequences as records were inserted or deleted. Although maintenance of sequential patterns for record modification can be performed by using the deletion procedure and then the insertion procedure, double the computation time of a single procedure is needed. In this paper, we attempt to apply the concept of pre-large sequences to maintain sequential patterns as records are modified. The proposed algorithm does not require rescanning original databases until the accumulative number of modified customer sequences exceeds a safety bound derived by a pre-large concept. As databases grow larger, the number of modified customer sequences allowed before database rescanning also needs to grow.","PeriodicalId":405340,"journal":{"name":"2002 IEEE International Conference on Data Mining, 2002. Proceedings.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Maintenance of sequential patterns for record modification using pre-large sequences\",\"authors\":\"Ching-Yao Wang, T. Hong, S. Tseng\",\"doi\":\"10.1109/ICDM.2002.1184031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In previous work we proposed incremental mining algorithms for maintenance of sequential patterns based on the concept of pre-large sequences as records were inserted or deleted. Although maintenance of sequential patterns for record modification can be performed by using the deletion procedure and then the insertion procedure, double the computation time of a single procedure is needed. In this paper, we attempt to apply the concept of pre-large sequences to maintain sequential patterns as records are modified. The proposed algorithm does not require rescanning original databases until the accumulative number of modified customer sequences exceeds a safety bound derived by a pre-large concept. As databases grow larger, the number of modified customer sequences allowed before database rescanning also needs to grow.\",\"PeriodicalId\":405340,\"journal\":{\"name\":\"2002 IEEE International Conference on Data Mining, 2002. Proceedings.\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 IEEE International Conference on Data Mining, 2002. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDM.2002.1184031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Conference on Data Mining, 2002. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDM.2002.1184031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Maintenance of sequential patterns for record modification using pre-large sequences
In previous work we proposed incremental mining algorithms for maintenance of sequential patterns based on the concept of pre-large sequences as records were inserted or deleted. Although maintenance of sequential patterns for record modification can be performed by using the deletion procedure and then the insertion procedure, double the computation time of a single procedure is needed. In this paper, we attempt to apply the concept of pre-large sequences to maintain sequential patterns as records are modified. The proposed algorithm does not require rescanning original databases until the accumulative number of modified customer sequences exceeds a safety bound derived by a pre-large concept. As databases grow larger, the number of modified customer sequences allowed before database rescanning also needs to grow.