Tech Mining makes exploitation of text databases meaningful to those who can gain from derived knowledge about emerging technologies. It begins with the premise that we have the information, the tools to exploit it, and the need for the resulting knowledge.
The information provided puts new capabilities at the hands of technology managers. Using the material present, these managers can identify and access the most valuable technology information resources (publications, patents, etc.); search, retrieve, and clean the information on topics of interest; and lower the costs and enhance the benefits of competitive technological intelligence operations.

"...useful to a variety of institutions, programs, and people." (E-STREAMS, August 2005)

"Two data mining practitioners explain how to use the available software tools…to quickly access the technological information needed to gain competitive advantage." (Research Technology Management, May-June 2005)

ALAN L. PORTER's major concentration is technology intelligence, forecasting, and assessment. He has led the development of "technology opportunity analysis"—mining electronic bibliographic data sources to generate intelligence on emerging technologies. He holds a BS in chemical engineering from the California Institute of Technology, and a PhD in engineering psychology from UCLA. He is currently Director, Research & Development, for Search Technology, Inc., in Norcross, Georgia.

SCOTT W. CUNNINGHAM worked for the Technology Policy & Assessment Center at the Georgia Institute of Technology. He has worked in industry as a data mining and machine learning consultant, working chiefly in the e-commerce and retail industries. He holds a BEng in engineering science and mechanics from Georgia Tech and a DPhil in science, technology, and innovation policy from the University of Sussex, UK. He currently serves as an assistant professor on the Technology, Policy, and Management faculty of TU Delft.