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Research And Application On A Topological Constraint Based Sequential Data Mining Approach

Posted on:2010-03-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z G WangFull Text:PDF
GTID:2178360278965712Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
The issue of fault location received extensive concern in the field of telecom network management. The data mining approaches are introduced to extract clues from the telecom alarm data for fault location.Aiming at the key problems in telecom data mining, we have made a comprehensive analysis on the telecom network and its data as well as the fault propagation, some important characteristics are discovered, and a fault location oriented network model is built to improve the traditional approaches in data transforming and data mining. An enhanced data mining algorithm is proposed to introduce the constraints in real world into the data mining procedures. A data mining tool (NETMiner) is implemented to benchmark the new algorithm, and our experiments show that the new algorithm is quite effective in improving the accuracy and efficiency of the PreFixSpan mining algorithm.
Keywords/Search Tags:frequent sequence, network topological constraints, the GSP algorithm, the PreFixSpan algorithm
PDF Full Text Request
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