自然语言处理和文本挖掘识别软件工程职位的知识概况:从简历中生成知识概况

Rogelio Valdez-Almada, O. M. Rodríguez-Elías, C�sar Enrique Rose-G�mez, Mar�a De Jes�s Vel�zquez-Mendoza, Samuel Gonz�lez-L�pez
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引用次数: 7

摘要

组织经常报告难以找到有技能的人来填补知识密集的职位空缺。由于软件工程职位中有一些这样的工作,在许多软件工程组织中,职位发布和雇用熟练的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,它可以帮助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。这个工具的目的是在开放工作职位时进行初步筛选。所有这些都是使用自然语言处理(NLP)和文本挖掘(TM)来分析简历和课程中的非结构化文本来完成的。本文提出了一种利用自然语言处理和TM识别软件工程岗位知识概况的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Natural Language Processing and Text Mining to Identify Knowledge Profiles for Software Engineering Positions: Generating Knowledge Profiles from Resumes
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.
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