Abstract:
At present, job vacancies appear in online job
vacancy repositories. They are available in the form of images
or in the form of Portable Digital Format Documents. Text
information is embedded in them. By mining that text
information, current dynamics of the job market can be
identified. As the Information Technology industry is dynamic,
it is worth understanding what associations exist between job
titles and technologies that frequently appear together, when
applying for a job. For this purpose two algorithms can be
used. They are Apriori algorithm and Frequent Pattern
Growth algorithm. Among these two algorithms, this study
emphasizes the importance of using Frequent Pattern Growth
algorithm because it has eliminated the issue of performing so
many scans in the database, which lead the Apriori algorithm
less efficient. Frequent Pattern Growth algorithm used to mine
association rules which exist between job titles and technologies
required for them. The aim of the study is to mine how
technologies appear associated with each other in job
vacancies. Job seekers can be aware of what technologies have
association trends in the job market and that would be helpful
to reduce the gap that exists between skills of job seekers and
industry demands.
