Abstract— The paper is dedicated to the application of web data extraction technologies to facilitate decision support. As the Internet becomes a scrapable representation of the real world, the need to utilize online data arises in mafny specialized fields that search engines generally won’t cover. The considerations on feasibility of employing automated web harvesting methods for obtaining data to populate decision-support systems’ databases are provided. Although the initial effort required for their implementation may be substantial, for certain domains they allow getting hold of information that otherwise would be too extensive for manual collection. We also provide a description of a project involving the construction of the system used for labour market management by regional authorities. The daily data extraction from job-related websites allows unprecedented precision of analysis and decision-making in the domain.

Index Terms— Artificial intelligence, data mining, information systems, web scraping.

M. Bakaev and T. Avdeenko are with the Economic Informatics department, Novosibirsk State Technical University, Novosibirsk, 630132, Russia (e-mail: maxis81@gmail.com, tavdeenko@mail.ru).

Cite: Maxim Bakaev and Tatiana Avdeenko, " Data Extraction for Decision-Support Systems: Application in Labour Market Monitoring and Analysis," International Journal of e-Education, e-Business, e-Management and e-Learning vol. 4, no. 1, pp. 23-27, 2014.