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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14247
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| Title: | Abstract-Driven Pattern Discovery In Databases |
| Authors: | Dhar, Vasant
Tuzhilin, Alexander |
| Keywords: | pattern discovery
data abstraction
classification
generalization |
| Issue Date: | 1993 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-93-11 |
| Abstract: | In this paper, we study the problem of discovering interesting patterns
in large volumes of data. Patterns can be expressed not only in terms of
the database schema but also in user-defined terms, such as relational
views and classification hierarchies. The user-defined terminology is
stored in a data dictionary that maps it into the language of the
database schema. We define a pattern as a deductive rule expressed in
user-defined terms that has a degree of certainty associated with it. We
present methods of discovering interesting patterns based on abstracts
which are summaries of the data expressed in the language of the user. |
| URI: | http://hdl.handle.net/2451/14247 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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