Interesting case of WhizBang! labs:

This startup attempted to use machine learning to mine large-scale data, and hired manyof the top machine-learning people to do so. Unfortunately, it was not able to survive. Why?

Following rationale was giving in the “mining of massive datasets” book:
machine learning has not proved successful in situations
where we can describe the goals of the mining more directly. An interesting case in point is the attempt by WhizBang! Labs1 to use machine learning to locate people’s resumes on theWeb. It was not able to do better than algorithms designed by hand to look for some of the obvious words and phrases that appear in the typical resume. Since everyone who has looked at or written a resume has
a pretty good idea of what resumes contain, there was no mystery about what makes a Web page a resume. Thus, there was no advantage to machine-learning over the direct design of an algorithm to discover resumes.

via Paras Doshi - Blog http://on.fb.me/WAQ5ky