Issue No. 01 - January/February (2010 vol. 27)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MS.2009.150
Chuck Litecky , Southern Illinois University, Carbondale
Andrew Aken , Southern Illinois University, Carbondale
Altaf Ahmad , Southern Illinois University, Carbondale
H. James Nelson , Southern Illinois University, Carbondale
Understanding the types of jobs, the skills used in those jobs, and the relative distribution of jobs available in the computing professions is imperative in today's economy. This article uses a Web content mining approach to address these information needs. With this approach, the authors identified 20 categories of current computing jobs and their associated skills needs. During the study period, they extracted and analyzed nearly a quarter million job ads from Monster.com, HotJobs.com, and SimplyHired.com. The resulting data will be useful to current computing professionals, prospective employees, human-resource executives, and educational institutions.
clustering, web mining, data mining, computer and information science education, employment, occupations, software, software engineering
A. Ahmad, A. Aken, H. J. Nelson and C. Litecky, "Mining for Computing Jobs," in IEEE Software, vol. 27, no. , pp. 78-85, 2009.