Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
We design a new yet efficient strategy for identifying against-expectation patterns in databases. An against-expectation pattern is either an itemset that its support is out of a certain neighbor of its expected value, referred to an against-expectation itemset or an association rule generating by an against-expectation itemset, referred to an against-expectation rule. The techniques for mining against-expectation patterns are previously undeveloped. Present algorithm for identifying against-expectation patterns is based on the nearest- neighbor graph and correlation analysis techniques. We experimentally evaluate our algorithms and demonstrate that our approach is efficient and promising.
How to cite this article:
Shujie Yang , Xiaofang You , Feng Chen and Shichao Zhang . Stock-management-based Expectation Pattern Discovery.
DOI: https://doi.org/10.36478/ajit.2005.1086.1092
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2005.1086.1092