{"title":"基于文本聚类的人力资源管理和信息系统趋势分析","authors":"B. Sohrabi, I. R. Vanani, Ehsan Abedin","doi":"10.4018/IJHCITP.2018070101","DOIUrl":null,"url":null,"abstract":"Human resources management has seen a significant change by the emergence of information systems from a traditional or popularly called personnel management to the modern one. The purpose of this article is to study the trends of information systems in the field of human resources management in combination with information systems through text mining approaches on a broad exploration of internationally published papers. Among text analytics methods for extracting trends, text clustering has been applied to the dataset of highly-ranked information systems journals. The data set was obtained from Scopus database for the period of 2013 to 2017. Afterwards, text clustering algorithms were applied and validated on the titles, abstracts and keywords. The results present practical and intuitive information which can help practitioners and scholars to grasp a useful overview and provides them with the opportunity to focus on trends in information systems in the field human resources management.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Human Resources Management and Information Systems Trend Analysis Using Text Clustering\",\"authors\":\"B. Sohrabi, I. R. Vanani, Ehsan Abedin\",\"doi\":\"10.4018/IJHCITP.2018070101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human resources management has seen a significant change by the emergence of information systems from a traditional or popularly called personnel management to the modern one. The purpose of this article is to study the trends of information systems in the field of human resources management in combination with information systems through text mining approaches on a broad exploration of internationally published papers. Among text analytics methods for extracting trends, text clustering has been applied to the dataset of highly-ranked information systems journals. The data set was obtained from Scopus database for the period of 2013 to 2017. Afterwards, text clustering algorithms were applied and validated on the titles, abstracts and keywords. The results present practical and intuitive information which can help practitioners and scholars to grasp a useful overview and provides them with the opportunity to focus on trends in information systems in the field human resources management.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJHCITP.2018070101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJHCITP.2018070101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human Resources Management and Information Systems Trend Analysis Using Text Clustering
Human resources management has seen a significant change by the emergence of information systems from a traditional or popularly called personnel management to the modern one. The purpose of this article is to study the trends of information systems in the field of human resources management in combination with information systems through text mining approaches on a broad exploration of internationally published papers. Among text analytics methods for extracting trends, text clustering has been applied to the dataset of highly-ranked information systems journals. The data set was obtained from Scopus database for the period of 2013 to 2017. Afterwards, text clustering algorithms were applied and validated on the titles, abstracts and keywords. The results present practical and intuitive information which can help practitioners and scholars to grasp a useful overview and provides them with the opportunity to focus on trends in information systems in the field human resources management.