Company Name Matching Using Job Market Data Enrichment

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 proxi...

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Vydáno v:IT professional Ročník 26; číslo 2; s. 76 - 82
Hlavní autor: Ternikov, Andrei A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Washington IEEE 01.03.2024
IEEE Computer Society
Témata:
Algorithm design and theory
Algorithms
Approximation algorithms
Companies
Data integration
Feature extraction
Labor market
Legal factors
Machine learning algorithms
Matching
Matching pursuit algorithms
Performance evaluation
Thresholds
Training
ISSN:1520-9202, 1941-045X
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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content type line 14
ISSN:1520-9202
1941-045X
DOI:10.1109/MITP.2024.3371179