Evidence based Employee Analytics using Taxonomy Enabled Knowledge Graph

Nitin Aggarwal, Sandeep Varma, Alina Rizvi, S. Shivam, Apuroop Bhushanam, Rishu Jamaiyar
{"title":"Evidence based Employee Analytics using Taxonomy Enabled Knowledge Graph","authors":"Nitin Aggarwal, Sandeep Varma, Alina Rizvi, S. Shivam, Apuroop Bhushanam, Rishu Jamaiyar","doi":"10.1109/DELCON57910.2023.10127301","DOIUrl":null,"url":null,"abstract":"Every organization produces a lot of data, analyzing this data, to gain insights and to make amendments is vital for running any sector. There are many documents that can be used to analyze the company’s staffing distribution. One such document is statement of work, this includes the staffing details, the client names, capabilities focused, assets and tools used in that specific project. In this paper we create a pipeline, by taking dataset comprised of all the sow documents generated by an organization and then generating insights from it. We created a utility to identify the expertise of every employee, this information can be used to further predict the employee similarity or to create an expertise-based search engine for employees. These tools can assist the management and staffing authorities at higher level. Hence, we can create a solution and save an enormous amount of human efforts and time.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DELCON57910.2023.10127301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Every organization produces a lot of data, analyzing this data, to gain insights and to make amendments is vital for running any sector. There are many documents that can be used to analyze the company’s staffing distribution. One such document is statement of work, this includes the staffing details, the client names, capabilities focused, assets and tools used in that specific project. In this paper we create a pipeline, by taking dataset comprised of all the sow documents generated by an organization and then generating insights from it. We created a utility to identify the expertise of every employee, this information can be used to further predict the employee similarity or to create an expertise-based search engine for employees. These tools can assist the management and staffing authorities at higher level. Hence, we can create a solution and save an enormous amount of human efforts and time.
基于证据的员工分析使用支持分类的知识图谱
每个组织都会产生大量数据,分析这些数据,以获得见解并进行修改对于任何部门的运营都至关重要。有很多文件可以用来分析公司的人员配置。其中一个文档是工作说明,它包括人员配置细节、客户名称、关注的功能、特定项目中使用的资产和工具。在本文中,我们创建了一个管道,通过获取由组织生成的所有sow文档组成的数据集,然后从中生成见解。我们创建了一个实用程序来识别每个员工的专业知识,该信息可用于进一步预测员工的相似性或为员工创建基于专业知识的搜索引擎。这些工具可以帮助更高级别的管理和人员配置当局。因此,我们可以创建一个解决方案,并节省大量的人力和时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信