{"title":"阶段:一种用于网络搜索的用户概要学习方法","authors":"A. Eckhardt, Tomáš Horváth, P. Vojtás","doi":"10.1109/WI.2007.146","DOIUrl":null,"url":null,"abstract":"Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"PHASES: A User Profile Learning Approach for Web Search\",\"authors\":\"A. Eckhardt, Tomáš Horváth, P. Vojtás\",\"doi\":\"10.1109/WI.2007.146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering.\",\"PeriodicalId\":192501,\"journal\":{\"name\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"volume\":\"207 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI.2007.146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2007.146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PHASES: A User Profile Learning Approach for Web Search
Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
