Company Name Matching Using Job Market Data Enrichment

IF 2.2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IT Professional Pub Date : 2024-05-02 DOI:10.1109/mitp.2024.3371179
Andrei A. Ternikov
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引用次数: 0

Abstract

This article contributes to the field of matching techniques by introducing a new algorithm based on labor market data enrichment. This approach is able to collect and balance the training and test samples for data integration purposes. By setting thresholds for textual matching and geographic proximity, it simplifies the process of finding suitable company matches. Based on insufficiently studied datasets, the experimental findings show that the performance evaluation of proposed models differs depending on the similarity thresholds used.
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利用就业市场丰富数据进行公司名称匹配
本文介绍了一种基于劳动力市场数据富集的新算法,为匹配技术领域做出了贡献。这种方法能够收集和平衡训练样本和测试样本,以达到数据整合的目的。通过设置文本匹配和地理接近的阈值,它简化了寻找合适匹配公司的过程。基于研究不足的数据集,实验结果表明,所使用的相似性阈值不同,所提议模型的性能评估也不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IT Professional
IT Professional COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
5.00
自引率
0.00%
发文量
111
审稿时长
>12 weeks
期刊介绍: IT Professional is a technical magazine of the IEEE Computer Society. It publishes peer-reviewed articles, columns and departments written for and by IT practitioners and researchers covering: practical aspects of emerging and leading-edge digital technologies, original ideas and guidance for IT applications, and novel IT solutions for the enterprise. IT Professional’s goal is to inform the broad spectrum of IT executives, IT project managers, IT researchers, and IT application developers from industry, government, and academia.
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