{"title":"从序列中挖掘频繁模式","authors":"Jun-yan Zhang, Fan Min","doi":"10.1109/ICCIAUTOM.2011.6183913","DOIUrl":null,"url":null,"abstract":"Pattern mining is a popular issue in biological sequence analysis. In this paper, we propose new definitions related to the pattern frequency, where gaps are mined instead of specified. We develop algorithm with polynomial complexities. Patterns can grow from both sides, and Apriori property holds. Some interesting biological patterns are mined by our algorithm.","PeriodicalId":177039,"journal":{"name":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Mining frequent patterns from sequences\",\"authors\":\"Jun-yan Zhang, Fan Min\",\"doi\":\"10.1109/ICCIAUTOM.2011.6183913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pattern mining is a popular issue in biological sequence analysis. In this paper, we propose new definitions related to the pattern frequency, where gaps are mined instead of specified. We develop algorithm with polynomial complexities. Patterns can grow from both sides, and Apriori property holds. Some interesting biological patterns are mined by our algorithm.\",\"PeriodicalId\":177039,\"journal\":{\"name\":\"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIAUTOM.2011.6183913\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2011.6183913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern mining is a popular issue in biological sequence analysis. In this paper, we propose new definitions related to the pattern frequency, where gaps are mined instead of specified. We develop algorithm with polynomial complexities. Patterns can grow from both sides, and Apriori property holds. Some interesting biological patterns are mined by our algorithm.
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