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        <identifier>oai:meral.edu.mm:recid/5060</identifier>
        <datestamp>2022-03-24T23:15:39Z</datestamp>
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          <dc:title>Discovering the Association Rules in Data Cube from Web Server Log Files</dc:title>
          <dc:creator>Kyaw, Phyo Tinzar</dc:creator>
          <dc:creator>Phyu, Sabai</dc:creator>
          <dc:description>Analyzing and exploring regularities in thebehavior of the web page reader is imprinted onthe web server log files can improve systemperformance; enhance the quality and delivery ofInternet information services to the end user.Webmining techniques can use to search for webaccess patterns, web structures, regularity anddynamics of web contents. OLAP (OnlineAnalytical Processing)-based association rulemining integrates OLAP and association rulemining that facilitates flexible mining ofinteresting knowledge in data cube because it canbe performed at multilevel or multidimensional indata cube.In this system, Web log database is usedto store web log records of log files collected fromweb server. And web log database are constructedvia a process of data cleaning, datatransformation. Data cube will be implementedfrom log files.Generating rules from data cubewill reduce counting phase of association rulesince it stores the pre-computed countvalues.Frequent patterns are generated based ondimensions of the web logs instead of page itemsets.The generated frequent patterns can later beapplied to improve web site management, decisionmaking process.</dc:description>
          <dc:date>2017-12-27</dc:date>
          <dc:identifier>http://hdl.handle.net/20.500.12678/0000005060</dc:identifier>
          <dc:identifier>https://meral.edu.mm/records/5060</dc:identifier>
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