{"title":"基于人工免疫系统的新闻文章推荐","authors":"B. Mihaljević, I. Cavrak, M. Žagar","doi":"10.1109/ITI.2005.1491158","DOIUrl":null,"url":null,"abstract":"Artificial immune systems are solution finding techniques often used for classification and recommendation problems. Danger theory is one of new context dependant response theories of how an artificial immune system responds to pathogens. News articles recommendation systems solve problems of presenting articles with interesting topics to user honoring evolving user preferences and past choices. This paper describes how artificial immune system with Danger theory can be utilized for news articles recommendation on Web portals or similar media presenter systems and presents algorithm and method for handling user preferences and article features in recommender system.","PeriodicalId":392003,"journal":{"name":"27th International Conference on Information Technology Interfaces, 2005.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An artificial immune system approach to news article recommendation\",\"authors\":\"B. Mihaljević, I. Cavrak, M. Žagar\",\"doi\":\"10.1109/ITI.2005.1491158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial immune systems are solution finding techniques often used for classification and recommendation problems. Danger theory is one of new context dependant response theories of how an artificial immune system responds to pathogens. News articles recommendation systems solve problems of presenting articles with interesting topics to user honoring evolving user preferences and past choices. This paper describes how artificial immune system with Danger theory can be utilized for news articles recommendation on Web portals or similar media presenter systems and presents algorithm and method for handling user preferences and article features in recommender system.\",\"PeriodicalId\":392003,\"journal\":{\"name\":\"27th International Conference on Information Technology Interfaces, 2005.\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"27th International Conference on Information Technology Interfaces, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITI.2005.1491158\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th International Conference on Information Technology Interfaces, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITI.2005.1491158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An artificial immune system approach to news article recommendation
Artificial immune systems are solution finding techniques often used for classification and recommendation problems. Danger theory is one of new context dependant response theories of how an artificial immune system responds to pathogens. News articles recommendation systems solve problems of presenting articles with interesting topics to user honoring evolving user preferences and past choices. This paper describes how artificial immune system with Danger theory can be utilized for news articles recommendation on Web portals or similar media presenter systems and presents algorithm and method for handling user preferences and article features in recommender system.
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