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Natural Language Processing and Text Mining to Identify Knowledge Profiles for Software Engineering Positions: Generating Knowledge Profiles from Resumes

机译:自然语言处理和文本挖掘,以确定软件工程位置的知识配置文件:从恢复生成知识概况

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Organizations frequently report problems finding skillful people to cover their most knowledge intensive vacancies. Being software engineering positions some of the such kind of jobs, there is a considerable gap between job postings and hiring skillful engineers in many software engineering organizations. In this paper, we will introduce the prototype of a web application that helps identifying Technical Knowledge (TK) in software development, to serve as a tool in the hiring process of software engineering positions, and in talent management. The purpose of this tool is to do an initial screening when opening a job position. All this is accomplished using Natural Language Processing (NLP) and Text Mining (TM) to analyze unstructured text in resumes and curriculum. We propose a way to use NLP and TM to identify knowledge profiles for Software Engineering Positions.
机译:组织经常报告问题发现熟练的人们涵盖他们最知识的密集型空缺。作为软件工程占据一些这样的工作,在许多软件工程组织中招聘帖子和雇用熟练工程师之间存在相当大的差距。在本文中,我们将介绍一个Web应用程序的原型,有助于识别软件开发中的技术知识(TK),作为软件工程职位招聘过程中的工具,以及人才管理。该工具的目的是在打开作业位置时进行初始筛选。所有这些都是使用自然语言处理(NLP)和文本挖掘(TM)完成的,以分析恢复和课程中的非结构化文本。我们提出了一种方法来使用NLP和TM来识别软件工程位置的知识配置文件。

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