Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39983
Title: Mining weak rules
Authors: Liu, Huan 
Lu, Hongjun 
Issue Date: 1999
Source: Liu, Huan,Lu, Hongjun (1999). Mining weak rules. Proceedings - IEEE Computer Society's International Computer Software and Applications Conference : 309-310. ScholarBank@NUS Repository.
Abstract: Finding patterns from data sets is a fundamental task of data mining. If we categorize all patterns into strong, weak, and random, conventional data mining techniques are designed only to find strong patterns, which hold for numerous objects and are usually consistent with the expectations of experts. In this paper, we address the problem of finding weak patterns (i.e., reliable exceptions) from databases. They are valid for a small number of objects. A simple approach is proposed which uses deviation analysis to identify interesting exceptions and explore reliable ones. Besides, it is flexible in handling both subjective and objective exceptions. We demonstrate the effectiveness of the proposed approach through a benchmark data set.
Source Title: Proceedings - IEEE Computer Society's International Computer Software and Applications Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/39983
ISSN: 07303157
Appears in Collections:Staff Publications

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