{"title":"作为数据库方案设计的行为发现","authors":"T. Miura, I. Shioya, Kohei Watanabe","doi":"10.1109/TIME.2000.856592","DOIUrl":null,"url":null,"abstract":"In this investigation, we propose an inductive classification method for a collection of temporal information which mean behavior. We assume a Markov property and discuss ergodic analysis by which we can extract stationary parts of the behavior. We discuss a design methodology for database schemes based on the theory.","PeriodicalId":130990,"journal":{"name":"Proceedings Seventh International Workshop on Temporal Representation and Reasoning. TIME 2000","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Behavior discovery as database scheme design\",\"authors\":\"T. Miura, I. Shioya, Kohei Watanabe\",\"doi\":\"10.1109/TIME.2000.856592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this investigation, we propose an inductive classification method for a collection of temporal information which mean behavior. We assume a Markov property and discuss ergodic analysis by which we can extract stationary parts of the behavior. We discuss a design methodology for database schemes based on the theory.\",\"PeriodicalId\":130990,\"journal\":{\"name\":\"Proceedings Seventh International Workshop on Temporal Representation and Reasoning. TIME 2000\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Seventh International Workshop on Temporal Representation and Reasoning. TIME 2000\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TIME.2000.856592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Seventh International Workshop on Temporal Representation and Reasoning. TIME 2000","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIME.2000.856592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this investigation, we propose an inductive classification method for a collection of temporal information which mean behavior. We assume a Markov property and discuss ergodic analysis by which we can extract stationary parts of the behavior. We discuss a design methodology for database schemes based on the theory.