{"title":"Book recommendation based on web social network","authors":"Ming-jian Zhou","doi":"10.1109/ICAIE.2010.5641415","DOIUrl":null,"url":null,"abstract":"Recommender systems play an important role in dealing with web information overload such as book e-commerce. Current recommender systems often generate recommendation on users' opinions on items, and have several fatal weaknesses. With the growth of web social networks, a new kind of information is available: trust rating expressed by an user on another user. The web-based nature of this information makes it ideal for use in a variety of intelligent systems that can take advantage of the users' social and personal data. In this paper, we analysis the problem of trust in social network, then propose a recommender system model based on social network trust and discuss the recommender methods‥","PeriodicalId":216006,"journal":{"name":"2010 International Conference on Artificial Intelligence and Education (ICAIE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Artificial Intelligence and Education (ICAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIE.2010.5641415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Recommender systems play an important role in dealing with web information overload such as book e-commerce. Current recommender systems often generate recommendation on users' opinions on items, and have several fatal weaknesses. With the growth of web social networks, a new kind of information is available: trust rating expressed by an user on another user. The web-based nature of this information makes it ideal for use in a variety of intelligent systems that can take advantage of the users' social and personal data. In this paper, we analysis the problem of trust in social network, then propose a recommender system model based on social network trust and discuss the recommender methods‥