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Meshack Muderedzwa, Emanuel Nyakwende (2010)
A framework for improving the effectiveness of IT in employment screening2010 IEEE Student Conference on Research and Development (SCOReD)
(2016)
The Concept Industry 4.0: An Empirical Analysis of Technologies and Applications in Production
(2015)
and the consequences for labour market and economy
C. Aggarwal, ChengXiang Zhai (2012)
Mining Text Data
G. Kochenberger, F. Glover, B. Alidaee, Haibo Wang (2005)
Clustering of Microarray data via Clique PartitioningJournal of Combinatorial Optimization, 10
André Klahold, Patrick Uhr, Fazel Ansari, M. Fathi (2014)
Using Word Association to Detect Multitopic Structures in Text DocumentsIEEE Intelligent Systems, 29
Dan Jurafsky, James Martin (2000)
Speech and language processing: an introduction to natural language processing
(2012)
Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection, Springer Science & Business Media
G. Kucherov, Dekel Tsur (2013)
Approximate String Matching using a Bidirectional Index
Online, available at: www.textkernel.com/hr-software-modules/bidirectionalmatching
L. Rasmussen (1992)
In information retrieval: data structures and algorithms
S. Fortunato (2009)
Community detection in graphsArXiv, abs/0906.0612
Per Capita, E. Dawson, Myfan Jordan (1995)
About the authorsMachine Vision and Applications, 1
Hmway Tar, Thi Nyaunt (2011)
Ontology-based Concept Weighting for Text DocumentsWorld Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 5
J. Dunlop (1966)
Job Vacancy Measures and Economic Analysis
(2011)
Emerging Careers and How to Create Them: 70 Jobs for 2030
Iftikhar Hussain, S. Kazmi, Israr Khan, R. Mehmood (2013)
Improved-Bidirectional Exact Pattern Matching
(1999)
An analysis of recent works on clustering algorithms
Fazel Ansari, Ulrich Seidenberg (2016)
A Portfolio for Optimal Collaboration of Human and Cyber Physical Production Systems in Problem-Solving.International Association for Development of the Information Society
M. Beblavý, Anette Thum (2013)
Online job vacancy data as a source for micro-level analysis of employers' preferences. A methodological enquiry. 1
S. Chala, Fazel Ansari, M. Fathi (2016)
A Framework for Enriching Job Vacancies and Job Descriptions Through Bidirectional Matching
C. Aggarwal (2017)
Graph Clustering
(2013)
The magic of headhunting: a how-to guide to hunting and closing top candidates
Guojun Gan, Chaoqun Ma, Jianhong Wu (2007)
Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
Fausto Giunchiglia, Mikalai Yatskevich, P. Shvaiko (2007)
Semantic Matching: Algorithms and ImplementationJ. Data Semant., 9
Yung-Shen Lin, Jung-Yi Jiang, Shie-Jue Lee (2014)
A Similarity Measure for Text Classification and ClusteringIEEE Transactions on Knowledge and Data Engineering, 26
(2015)
Ways to make your resume perfect for a job opening
Muhammad Rafi, M. Shaikh (2013)
An improved semantic similarity measure for document clustering based on topic mapsArXiv, abs/1303.4087
Lucia Kureková, M. Beblavý, A. Thum (2014)
Using Internet Data to Analyse the Labour Market: A Methodological EnquiryMacroeconomics: Employment
A. Hotho, A. Maedche, Steffen Staab (2001)
Text clustering based on good aggregationsProceedings 2001 IEEE International Conference on Data Mining
Xiquan Yang, Dina Guo, XueYa Cao, JianYuan Zhou (2008)
Research on Ontology-Based Text Clustering2008 Third International Workshop on Semantic Media Adaptation and Personalization
(2012)
Structure Discovery in Natural Language, Springer
Michele Belloni, A. Brugiavini, E. Meschi, K. Tijdens (2016)
Measuring and Detecting Errors in Occupational Coding: an Analysis of SHARE DataJournal of Official Statistics, 32
Jian Ma, Wei Xu, Yong-Hong Sun, E. Turban, Shouyang Wang, Ou Liu (2012)
An Ontology-Based Text-Mining Method to Cluster Proposals for Research Project SelectionIEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 42
(2012)
International Standard Classification of Occupations ISCO-08
(2013)
Emerging career trends for information professionals: a snapshot of job titles in summer
A. Fahad, Najlaa Alshatri, Z. Tari, A. Alamri, I. Khalil, Albert Zomaya, S. Foufou, Abdelaziz Bouras (2014)
A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical AnalysisIEEE Transactions on Emerging Topics in Computing, 2
(2009)
Bidirectional string matching algorithm in text mining
(2015)
How to match qualifications to a job description in a resume
Stackexchange data dump
S. Rajasekaran (2005)
Efficient parallel hierarchical clustering algorithmsIEEE Transactions on Parallel and Distributed Systems, 16
Xiaobo Li (1990)
Parallel Algorithms for Hierarchical Clustering and Cluster ValidityIEEE Trans. Pattern Anal. Mach. Intell., 12
(2015)
ESCO home European commission
(2016)
Sample individual skills profile
M. Wolter, A. Mönnig, Markus Hummel, Christian Schneemann, Enzo Weber, Gerd Zika, R. Helmrich, T. Maier, Caroline Neuber-Pohl (2015)
IAB Forschungsbericht Results from the project work of IAB 8 / 2015 Industry 4 . 0 and the consequences for labour market and economy Scenario calculations in line with the BIBB-IAB qualifications and occupational field projections
(2014)
Understanding online job ads data: a technical report
(2015)
Salary checks -worldwide wage comparison
Michele Belloni, A. Brugiavini, E. Meschi, K. Tijdens, K. Tijdens (2014)
Measurement Error in Occupational Coding:An Analysis on Share DataEconometrics: Data Collection & Data Estimation Methodology eJournal
Leigh Branham (2005)
The 7 Hidden Reasons Employees Leave: How to Recognize the Subtle Signs and Act Before It's Too Late
Künstliche Intelligenz, 16
Jianhui Chen, Jianhua Ma, N. Zhong, Yiyu Yao, Jiming Liu, Runhe Huang, Wenbin Li, Zhisheng Huang, Yang Gao (2014)
WaaS: Wisdom as a ServiceIEEE Intelligent Systems, 29
(2016)
What are the most successful job search strategies for 2015 - 2016 ? ”
(2015)
The Internet of Things, MIT press
She studied Sociology and Psychology at Groningen University, and obtained her PhD in Sociology in 1989. She is the scientific coordinator WageIndicator and a member of Webdatanet
S. Ceri, A. Bozzon, Marco Brambilla, Emanuele Valle, P. Fraternali, S. Quarteroni (2013)
An Introduction to Information Retrieval
International Journal of Human Factors and Ergonomics, 4
(2009)
How to manage headhunters for candidates
Journal of Computer Science Review, 1
S. Chala, Fazel Ansari, M. Fathi (2016)
Towards implementing context-aware dynamic text field for web-based data collection, 4
PurposeThe purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker qualifications and skills, against the vacancy provided by employers or job-agents.Design/methodology/approachThe paper presents a framework of bidirectional jobseeker-to-vacancy matching system. Using occupational data from various sources such as the WageIndicator web survey, International Standard Classification of Occupations, European Skills, Competences, Qualifications, and Occupations as well as vacancy data from various open access internet sources and job seekers information from social networking sites, the authors apply machine learning techniques for bidirectional matching of job vacancies and occupational standards to enhance the contents of job vacancies and job seekers profiles. The authors also apply bidirectional matching of job seeker profiles and vacancies, i.e., semantic matching vacancies to job seekers and vice versa in the individual level. Moreover, data from occupational standards and social networks were utilized to enhance the relevance (i.e. degree of similarity) of job vacancies and job seekers, respectively.FindingsThe paper provides empirical insights of increase in job vacancy advertisements on the selected jobs – Internet of Things – with respect to other job vacancies, and identifies the evolution of job profiles and its effect on job vacancies announcements in the era of Industry 4.0. In addition, the paper shows the gap between job seeker interests and available jobs in the selected job area.Research limitations/implicationsDue to limited data about jobseekers, the research results may not guarantee high quality of recommendation and maturity of matching results. Therefore, further research is required to test if the proposed system works for other domains as well as more diverse data sets.Originality/valueThe paper demonstrates how online jobseeker-to-vacancy matching can be improved by use of semantic technology and the integration of occupational standards, web survey data, and social networking data into user profile collection and matching.
International Journal of Manpower – Emerald Publishing
Published: Nov 5, 2018
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