Data mining analysis of online job advertisements

OData support
Supervisor:
Nagy István
Department of Telecommunications and Media Informatics

In the last few years, job seeking became a significant factor in people’s life, especially since the financial crisis has broken out and the majority of people have lost their job. The number of unemployed persons who are active in job seeking continues to grow almost all over the world despite the fact that the number of educated people is increasing. Thus for them also it can mean a business advantage the knowledge which is explored about expectations of qualifications in the related job field, and possess all the information which is relevant in this field.

My task in this semester it was to choose one of the largest online job vacancy companies, whose unstructured job advertisements can be extracted and stored in structured mode. Furthermore the storing process of these unstructured data should be based on data warehouse concept, in order to make efficient analysis in the future. I have used a data mining software on the whole process of implementation. After I have automatized the data extracting and storing processes, on the base of collected data I have built a baseline predictive model, which helps to predict the job advertisements’ expected payment.

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