{"title":"基于上下文的集成模型","authors":"I. Nikolova","doi":"10.1145/2516775.2516791","DOIUrl":null,"url":null,"abstract":"The paper represents inference model that combines results from several different data sources. The model makes exclusive use of context properties as context is used to determine the mode different sources are combined. The mode of combining is dynamically set regarding both global and local characteristics of the context. This complicated combination schema is used in order to achieve better accuracy. The model is represented by factor graph with tree structure. That is a flexible implementation, which allows us to incorporate context usage in well-defined manner throughout inference process.","PeriodicalId":316788,"journal":{"name":"International Conference on Computer Systems and Technologies","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Context-based ensemble model\",\"authors\":\"I. Nikolova\",\"doi\":\"10.1145/2516775.2516791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper represents inference model that combines results from several different data sources. The model makes exclusive use of context properties as context is used to determine the mode different sources are combined. The mode of combining is dynamically set regarding both global and local characteristics of the context. This complicated combination schema is used in order to achieve better accuracy. The model is represented by factor graph with tree structure. That is a flexible implementation, which allows us to incorporate context usage in well-defined manner throughout inference process.\",\"PeriodicalId\":316788,\"journal\":{\"name\":\"International Conference on Computer Systems and Technologies\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computer Systems and Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2516775.2516791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computer Systems and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2516775.2516791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper represents inference model that combines results from several different data sources. The model makes exclusive use of context properties as context is used to determine the mode different sources are combined. The mode of combining is dynamically set regarding both global and local characteristics of the context. This complicated combination schema is used in order to achieve better accuracy. The model is represented by factor graph with tree structure. That is a flexible implementation, which allows us to incorporate context usage in well-defined manner throughout inference process.