{"title":"基于最大边际相关性的产品定制推荐","authors":"Chun-Ho Wu, Yue Wang, J. Ma","doi":"10.1080/17517575.2021.1992018","DOIUrl":null,"url":null,"abstract":"ABSTRACT Customised product design is attracting increasing attention. However, consumers can be overwhelmed by the variety of products. To confront this challenge, this paper presents a two-step recommendation approach for customised products. First, an adaptive specification process captures customer requirements in an accelerated manner by presenting the most informative attribute for a customer to specify. Then, a maximal marginal relevance-based recommendation set is presented, based on the customer’s partial specifications. This process ensures broad coverage of customers’ needs by considering not only the relevance of each product to their requirements but also redundancy in the recommendation set.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Maximal Marginal Relevance-Based Recommendation for Product Customisation\",\"authors\":\"Chun-Ho Wu, Yue Wang, J. Ma\",\"doi\":\"10.1080/17517575.2021.1992018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Customised product design is attracting increasing attention. However, consumers can be overwhelmed by the variety of products. To confront this challenge, this paper presents a two-step recommendation approach for customised products. First, an adaptive specification process captures customer requirements in an accelerated manner by presenting the most informative attribute for a customer to specify. Then, a maximal marginal relevance-based recommendation set is presented, based on the customer’s partial specifications. This process ensures broad coverage of customers’ needs by considering not only the relevance of each product to their requirements but also redundancy in the recommendation set.\",\"PeriodicalId\":11750,\"journal\":{\"name\":\"Enterprise Information Systems\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2021-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Enterprise Information Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/17517575.2021.1992018\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Enterprise Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/17517575.2021.1992018","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Maximal Marginal Relevance-Based Recommendation for Product Customisation
ABSTRACT Customised product design is attracting increasing attention. However, consumers can be overwhelmed by the variety of products. To confront this challenge, this paper presents a two-step recommendation approach for customised products. First, an adaptive specification process captures customer requirements in an accelerated manner by presenting the most informative attribute for a customer to specify. Then, a maximal marginal relevance-based recommendation set is presented, based on the customer’s partial specifications. This process ensures broad coverage of customers’ needs by considering not only the relevance of each product to their requirements but also redundancy in the recommendation set.
期刊介绍:
Enterprise Information Systems (EIS) focusses on both the technical and applications aspects of EIS technology, and the complex and cross-disciplinary problems of enterprise integration that arise in integrating extended enterprises in a contemporary global supply chain environment. Techniques developed in mathematical science, computer science, manufacturing engineering, and operations management used in the design or operation of EIS will also be considered.