{"title":"基于关联规则挖掘的小型在线零售商产品推荐系统","authors":"Junnan Chen, Courtney Miller, Gaby G. Dagher","doi":"10.1109/IDAM.2014.6912673","DOIUrl":null,"url":null,"abstract":"Recommendation systems in e-commerce have become essential tools to help businesses increase their sales. In this paper, we detail the design of a product recommendation system for small online retailers. Our system is specifically designed to address the needs of retailers with small data pools and limited processing power, and is tested for accuracy, efficiency, and scalability on real life data from a small online retailer.","PeriodicalId":135246,"journal":{"name":"Proceedings of the 2014 International Conference on Innovative Design and Manufacturing (ICIDM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Product recommendation system for small online retailers using association rules mining\",\"authors\":\"Junnan Chen, Courtney Miller, Gaby G. Dagher\",\"doi\":\"10.1109/IDAM.2014.6912673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recommendation systems in e-commerce have become essential tools to help businesses increase their sales. In this paper, we detail the design of a product recommendation system for small online retailers. Our system is specifically designed to address the needs of retailers with small data pools and limited processing power, and is tested for accuracy, efficiency, and scalability on real life data from a small online retailer.\",\"PeriodicalId\":135246,\"journal\":{\"name\":\"Proceedings of the 2014 International Conference on Innovative Design and Manufacturing (ICIDM)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2014 International Conference on Innovative Design and Manufacturing (ICIDM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAM.2014.6912673\",\"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 of the 2014 International Conference on Innovative Design and Manufacturing (ICIDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAM.2014.6912673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Product recommendation system for small online retailers using association rules mining
Recommendation systems in e-commerce have become essential tools to help businesses increase their sales. In this paper, we detail the design of a product recommendation system for small online retailers. Our system is specifically designed to address the needs of retailers with small data pools and limited processing power, and is tested for accuracy, efficiency, and scalability on real life data from a small online retailer.
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