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CourseTitle CourseID Instructor DataMiningoverStructuredandUn-StructuredData CIT-653 Dr.SamhaaEl-Beltagy CIT-INFORMATICS Elective SpringSemester,2015 Program Type StartOffering Pre-requisites: “IntroductiontoMachineLearningandStatisticalDataAnalysis” BriefDescription DataMininggenerallyreferstotheprocessofexploringpatternsandregularitiesin dataforenablingforecasting,predication,andprovidingabetterunderstandingof thedataforguidingdecisionmaking.Thiscourseprovidesanintroductiontodata mining concepts over structured and un-structured data with special emphasis on practicalapplicationsofthisimportantresearcharea.DataMiningusuallyinvolves the extraction and discovery of useful knowledge from raw data. The discovery process, also known as knowledge discovery, includes feature selection, data cleaning,andcodingandentailstheuseofdifferentstatisticalandmachinelearning techniques. The course will cover these areas. Throughout the whole process, students will be provided with examples which will serve to illustrate concepts being introduced. Students will also learn how to solve real-life problems using state-of-the-arttechnologiesfordataanalyses. GradingSystem 10%Attendanceandparticipation 15%Midterm 40%Assignmentsandprojects 25%Final Textbook “MiningofMassiveDataset,"byAnandRajaramanandJeffreyD.Ullman;Cambridge UniversityPress,2011. “DataMining:PracticalMachineLearningToolsandTechniques(SecondEdition)”byIan H.WittenandEibeFrank,MorganKaufmann,2005. COURSECONTENTS • • • • • • • • Dataminingconcepts SimilarityMeasuresonbigscale Miningdatastreams Webanalytics:pagerank,extractingknowledgefromtheweb,spam analysis Datacleaningandpre-processing Associationrulemining Advertisingontheweb Recommendationsystemsfore-commerce