Intelligent text analysis using natural language processing for competency-based recruitment

该项目的主要重点是为SkyHave Technologies Inc.(合作伙伴**公司)开发的创新招聘软件平台开发文本分类和自然语言处理**框架。这将涉及基于机器的文本分析，以根据提取的关键字和周围单词的上下文自动从求职申请中识别能力。合作伙伴公司**开发了一个基于技能的平台，以提高招聘过程的效率和可靠性。这个**平台可以供工人和用人单位根据招聘广告和**求职者技能找到最佳匹配。它处理广告，并将其分解为所需的技能，并根据候选人的技能对**候选人个人资料进行分类。然后进行机器学习，以提供匹配的结果。**这使应聘者能够近乎实时地识别机会，而不是传统方法的几天、几周甚至几个月**，并使招聘过程为平台用户带来回报，因为它快速且**具有成本效益。该平台还根据有针对性的技能**发展向工人推荐培训计划。尽管雇主可以使用该平台根据技能匹配来确定候选人，但由于必须在**应用程序上执行的任务复杂，查找**能力匹配结果是无法管理的。这降低了平台效用，并对匹配率产生了负面影响。该项目将**使该平台能够**根据文本分类向雇主提供基于能力的建议**工作说明与系统上创建的用户简档之间的匹配。例如，寻求**关系、创新、领导力、冒险和决策等核心能力的雇主将**自动收到所有活跃的相关申请者的通知。此外，特定职位的工资水平将**确定，并与应聘者的工资期望相匹配。该项目将大大提高基于技能的招聘的**质量，并增加平台内的用户参与度。

The main focus of the project is the development of a text classification and natural language processing**framework for an innovative recruiting software platform developed by SkyHive Technologies Inc. (partner**company). This will involve machine-based analysis of text to automatically identify competencies from job**applications according to extracted keywords and the context of surrounding words. The partner company has**developed a skills-based platform to increase the efficiency and reliability of the recruiting process. This**platform can be used by workers and employers to find the best matches according to job advertisements and**candidate skills. It processes advertisements and decomposes them into the required skills and categorizes**candidate profiles according to their skills. Machine learning is then performed to provide matching results.**This allows candidates to identify opportunities in near real-time as opposed to days, weeks or even months**with conventional approaches, and makes the hiring process rewarding for platform users as it is fast and**cost-effective. The platform also recommends training programs to workers according to targeted skill**development. Although employers can use the platform to identify candidates based on skill matching, finding**competency-matching results is unmanageable due to the complexity of tasks that must be performed on the**applications. This reduces the platform utility, and negatively impacts the matching rate. This project will**enable the platform to provide competency-based recommendations to employers based on text classification**matches between job descriptions and user profiles created on the system. For example, an employer who seeks**core competencies such as relationships, innovation, leadership, risk-taking, and decision-making will**automatically be notified of all active related applicants. Further, the salary levels for particular positions will**be determined and matched with the salary expectations of candidates. This project will greatly improve the**quality of the skills-based recruitment and increase user engagement within the platform.