{"title":"基于大数据分析用户特征的多种图书推荐算法比较","authors":"Ruixia Wang, Na He","doi":"10.1080/07317131.2023.2259691","DOIUrl":null,"url":null,"abstract":"Through big data analysis of borrowing information, it is possible to find the characteristics of different users. This paper applied K-means clustering to classify users. User feature vectors were...","PeriodicalId":43138,"journal":{"name":"Technical Services Quarterly","volume":"7 3","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Multiple Book Recommendation Algorithms After Analysis of User Characteristics Using Big Data\",\"authors\":\"Ruixia Wang, Na He\",\"doi\":\"10.1080/07317131.2023.2259691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Through big data analysis of borrowing information, it is possible to find the characteristics of different users. This paper applied K-means clustering to classify users. User feature vectors were...\",\"PeriodicalId\":43138,\"journal\":{\"name\":\"Technical Services Quarterly\",\"volume\":\"7 3\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technical Services Quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/07317131.2023.2259691\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technical Services Quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/07317131.2023.2259691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Comparison of Multiple Book Recommendation Algorithms After Analysis of User Characteristics Using Big Data
Through big data analysis of borrowing information, it is possible to find the characteristics of different users. This paper applied K-means clustering to classify users. User feature vectors were...
期刊介绍：
Technical Services Quarterly is dedicated to providing a forum for the presentation of current developments and future trends concerning the technical operations of libraries and information centers. The journal aims to keep its readers informed of current developments and future trends in research, developments, and practical implementation of systems and applications of traditional and non-traditional technical services and the public operations they influence and sustain. The journal accepts original research, theoretical, and implementation articles pertaining to technical services, automation, networking, document delivery, information technology, library instruction and information literacy, reference and bibliography, case studies, cost analysis, staffing, etc.
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