Abstract:
. Mining for association rules in market basket data has proved a fruitful area of research. Measures such as conditional probability (confidence) and correlation have been used to infer rules of the form "the existence of item A implies the existence of item B." However, such rules indicate only a statistical relationship between A and B. They do not specify the nature of the relationship: whether the presence of A causes the presence of B, or the converse, or some other attribute or phenomenon causes both to appear together. In applications, knowing such causal relationships is extremely useful for enhancing understanding and effecting change. While distinguishing causality from correlation is a truly difficult problem, recent work in statistics and Bayesian learning provide some avenues of attack. In these fields, the goal has generally been to learn complete causal models, which are essentially impossible to learn in large-scale data mining applications with a large number of varia...
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received his B.S. degree in mathematics and computer science from the University of Maryland at College Park in
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Data Mining and Knowledge Discovery, 1(1997): 79119. [HGC94
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Craig Silverstein obtained an A.B. degree in Computer Science from Harvard University and is a Ph.D. candidate (on leave) in Computer Science at Stanford University. He is a recipient of a National Defense Science and Engineering Graduate fellowship and a
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is the Stanford W. Ascherman Professor of Engineering in the Department of Computer Science at Stanford. He received the B.S. degree from Columbia University
– Ullman
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to his appointment at Stanford in 1979, he was a member of the technical staff of Bell Laboratories from 1966-1969, and on the faculty of Princeton University between 1969 and 1979. From 1990-1994, he was chair of the Stanford Computer Science Department.
– Prior
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was elected to the National Academy of Engineering in 1989 and has held Guggenheim and Einstein Fellowships. He is the 1996 winner of the Sigmod Contributions Award and the 1998 winner of the Karl V. Karlstrom Outstanding Educator Award. He is the author
– Ullman
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