DocumentCode :
1363343
Title :
Mining for Computing Jobs
Author :
Litecky, Chuck ; Aken, Andrew ; Ahmad, Altaf ; Nelson, H. James
Author_Institution :
Southern Illinois Univ., Carbondale, IL, USA
Volume :
27
Issue :
1
fYear :
2010
Firstpage :
78
Lastpage :
85
Abstract :
A Web content mining approach identified 20 job categories and the associated skills needs prevalent in the computing professions. Using a Web content data mining application, we extracted almost a quarter million unique IT job descriptions from various job search engines and distilled each to its required skill sets. We statistically examined these, revealing 20 clusters of similar skill sets that map to specific job definitions. The results allow software engineering professionals to tune their skills portfolio to match those in demand from real computing jobs across the US to attain more lucrative salaries and more mobility in a chaotic environment.
Keywords :
Internet; data mining; information filtering; search engines; statistical analysis; IT job description extraction; Web content data mining application; chaotic environment; job search engines; software engineering professionals; statistical analysis; clustering; computer and information science education; data mining; employment; occupations; software; software engineering; web mining;
fLanguage :
English
Journal_Title :
Software, IEEE
Publisher :
ieee
ISSN :
0740-7459
Type :
jour
DOI :
10.1109/MS.2009.150
Filename :
5232798
Link To Document :
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