Knowledge Extraction (data mining) from Engineering Databases

A Sample Publications Include:

• Reich, Y., Fenves, S. J., and Subrahmanian, E. (1994), Flexible Extraction of Practical Knowledge from Bridge Databases, In Proceedings of the First Congress on Computing in Civil Engineering (Washington, DC), pp. 1014-1021.
  (Postscript file, 185K)

• Reich, Y., Karni, R., and Fournier, F. (1993), An Investigation of Machine Learning Approaches to Knowledge Extraction from Databases, In Proceedings of The 10th Israeli Symposium on Artificial Intelligence, Computer Vision, and Neural Networks, Basri, R., Schild, U. J., and Stein, Y. (eds.), pp. 119-128. Information Processing Association of Israel.
  (not available on-line)

• Reich, Y., Konda, S., Levy, S. N., Monarch, I., and Subrahmanian, E. (1993), New roles for machine learning in design, Artificial Intelligence in Engineering, 8(3):165-181.
  This paper is related to the topic of knowledge extraction from databases even if not a typical paper on the subject. This paper reviews the present way of using machine learning in design and criticize it as being restrictive. The underlying assumptions under present use are discussed and new ways in which machine learning can be used in design are discussed. The use of natural language processing (NLP) techniques is discussed as well as the use of multiple machine learning tools (multistrategy). The integration framework for all the techniques is, as you have already guessed ... n-dim. (Postscript file, 783K)

Some Pointers to Machine Learning and Knowledge Acquisition Information