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MINING USER ACCESS PATTERNSFROM NETWORK FLOW ON THE INTERNET

This thesis focuses on mining user access patterns from netflow database collected from the core router of a regional network center. We use the attributed relational graph representation to formulate user access patterns on the Internet, and then propose a procedure to generalize common connection patterns and detect deviation patterns with such methods as large graph generalization, error correcting graph matching, frontier identification and pattern base recognition. The major contributions of this thesis are on represeting the network connection with attributed relational graph and developing data mining tehcniques for identifying access paterns and detecting deviation. The results can be used for better managing regional network in order to improve user satification in using regional netwrok netwrok services.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0718100-133038
Date18 July 2000
CreatorsChang, Shih-Ta
ContributorsFu-Ren Lin, Nian-Shing Chen, Chin-Ping Wei
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0718100-133038
Rightsunrestricted, Copyright information available at source archive

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