{"title":"基于多目标排序算法的电子商务推荐系统","authors":"A. Hidayatullah, Media Ayu Anugerah","doi":"10.1109/ICCED.2018.00041","DOIUrl":null,"url":null,"abstract":"The rapid growth of the e-commerce technology has pushed companies to strategize their marketing tools and techniques in order to target what products or services that need to be offered to the consumers. One of good techniques companies used to stay ahead in their marketing is by analyzing their market segmentation based on their consumers’ data. Recommender systems are among the tools used by companies to analyze the huge data of their consumers to assist them in their marketing. This study proposes multiobjective ranked bandits as an algorithm to be used in a recommender system for e-commerce. The results show that the algorithm worked well as a recommender system in an ecommerce environment.","PeriodicalId":166437,"journal":{"name":"2018 International Conference on Computing, Engineering, and Design (ICCED)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Recommender System for E-Commerce Using Multi-objective Ranked Bandits Algorithm\",\"authors\":\"A. Hidayatullah, Media Ayu Anugerah\",\"doi\":\"10.1109/ICCED.2018.00041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid growth of the e-commerce technology has pushed companies to strategize their marketing tools and techniques in order to target what products or services that need to be offered to the consumers. One of good techniques companies used to stay ahead in their marketing is by analyzing their market segmentation based on their consumers’ data. Recommender systems are among the tools used by companies to analyze the huge data of their consumers to assist them in their marketing. This study proposes multiobjective ranked bandits as an algorithm to be used in a recommender system for e-commerce. The results show that the algorithm worked well as a recommender system in an ecommerce environment.\",\"PeriodicalId\":166437,\"journal\":{\"name\":\"2018 International Conference on Computing, Engineering, and Design (ICCED)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Computing, Engineering, and Design (ICCED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCED.2018.00041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computing, Engineering, and Design (ICCED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCED.2018.00041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Recommender System for E-Commerce Using Multi-objective Ranked Bandits Algorithm
The rapid growth of the e-commerce technology has pushed companies to strategize their marketing tools and techniques in order to target what products or services that need to be offered to the consumers. One of good techniques companies used to stay ahead in their marketing is by analyzing their market segmentation based on their consumers’ data. Recommender systems are among the tools used by companies to analyze the huge data of their consumers to assist them in their marketing. This study proposes multiobjective ranked bandits as an algorithm to be used in a recommender system for e-commerce. The results show that the algorithm worked well as a recommender system in an ecommerce environment.