Download Foundations and Applications of Data Mining - Yao

USC Viterbi School
of Engineering
CatalogueCourseDescription
INF553:FoundationsandApplicationsofData
Mining
Units:3
Term—Day—Time:
Fall2015–TT–9:30-10:50am(section32423D)
Fall2015–TT–5:00-6:20pm(section32444D)
Location:KAP163
Instructor:Yao-YiChiang
Office:AHFB55C
OfficeHours:Tuesdayafterclass
ContactInfo:[email protected],213-740-7618
Instructor:WenshengWu
Office:GER204
OfficeHours:TBD
ContactInfo:[email protected]
CourseProducer:PoojaAnand
Office:TBD
OfficeHours:TBD
ContactInfo:[email protected]
Grader:SiddharthMahendraDasani
Office:TBD
OfficeHours:TBD
ContactInfo:[email protected]
Dataminingandmachinelearningalgorithmsforanalyzingverylargedatasets.EmphasisonMap
Reduce.Casestudies.
ExpandedCourseDescription
Dataminingisafoundationalpieceofthedataanalyticsskillset.Atahighlevel,itallows
theanalysttodiscoverpatternsindata,andtransformitintoausableproduct.The
coursewillteachdataminingalgorithmsforanalyzingverylargedatasets.Itwillhavean
appliedfocus,inthatitismeantforpreparingstudentstoutilizetopicsindataminingto
solverealworldproblems.
RecommendedPreparation:INF550,INF551andINF552.Knowledgeofprobability,linear
algebra,basicprogramming,andmachinelearning.
Abasicunderstandingengineeringprinciplesisrequired,includingbasicprogramming
skills;familiaritywiththePythonlanguageisdesirable.Mostassignmentsaredesigned
fortheUnixenvironment;basicUnixskillswillmakeprogrammingassignmentsmuch
easier.Studentswillneedsufficientmathematicalbackground,includingprobability,
statistics,andlinearalgebra.Someknowledgeofmachinelearningishelpful,butnot
required.
CourseNotes
Thecoursewillberunasalectureclasswithstudentparticipationstronglyencouraged.Thereareweekly
readingsandstudentsareencouragedtodothereadingspriortothediscussioninclass.Allofthecourse
materials,includingthereadings,lectureslides,homeworkswillbepostedonline
TechnologicalProficiencyandHardware/SoftwareRequired
StudentsareexpectedtoknowhowtoprograminalanguagesuchasPython.Studentsarealsoexpected
tohavetheirownlaptopordesktopcomputerwheretheycaninstallandrunsoftwaretodotheweekly
homeworkassignments.
RequiredReadingsandSupplementaryMaterials
• Rajaraman,J.LeskovecandJ.D.Ullman,MiningofMassiveDatasets
o CambridgeUniversityPress,2012.
o Availablefreeat:http://infolab.stanford.edu/~ullman/mmds.html
Inadditiontothetextbook,studentsmaybegivenadditionalreadingmaterialssuchas
researchpapers.Studentsareresponsibleforallassignedreadingassignments.
DescriptionandAssessmentofAssignments
HomeworkAssignments
Therewillbe5homeworkassignments.Theassignmentsmustbedoneindividually.Eachassignmentis
gradedonascaleof0-100andthespecificrubricforeachassignmentisgivenintheassignment.
GradingBreakdown
Quizzes:Therewillbeweeklyquizzesbasedonthematerialfromtheweekbefore.Thereisnomid-term
forthisclass.
Homework:Therewillbe5homeworksbasedonthetopicsoftheclasseachweek.
FinalExam:Thereisafinalexamattheendofthesemestercoveringallofthematerialcoveredintheclass.
ClassParticipation:Studentsareexpectedtocometoclassandparticipateintheclassdiscussionsand
discussionboard.
GradingSchema:
Quizzes 30%
Homework
40%
Final: 25%
ClassParticipation
5%
__________________________________________
Total 100%
GradeswillrangefromAthroughF.Thefollowingisthebreakdownforgrading:
94-100=A
90–93=A-
87–89=B+
84–86=B
80–83=B-
77–79=C+
74-76=C
70-73=C-
67-69=D+
64-66=D
60-63=D-
Below60isanF
AssignmentSubmissionPolicy
Homeworkassignmentsaredueat11:59pmontheduedateandshouldbesubmittedinBlackboard.You
cansubmithomeworkuptooneweeklate,butyouwillloose20%ofthepossiblepointsforthe
assignment.Afteroneweek,theassignmentcannotbesubmitted.
CourseSchedule:AWeeklyBreakdown
Week
1
(8/24)
Topic
IntroductiontoDataMining,
MapReduce
2
(8/31)
3
(9/7)
MapReduce(cont.)
Frequentitemsetsand
Associationrules
4
(9/14)
5
(9/21)
Frequentitemsetsand
Associationrules
Shingling,Minhashing,
LocalitySensitiveHashing
6
(9/28)
7
(10/5)
Shingling,Minhashing,
LocalitySensitiveHashing
RecommendationSystems:
Content-basedand
CollaborativeFiltering
RecommendationSystems:
Content-basedand
CollaborativeFiltering
Ch3:FindingSimilarItems
9
(10/19)
10
(10/26)
Clustering
Ch7:Clustering
LinkAnalysis:PageRank,
WebspamandTrustRank,
RandomWalkswithRestarts
Ch5:LinkAnalysis
11
(11/2)
12
(11/9)
AnalysisofMassiveGraphs
(SocialNetworks)
AnalysisofMassiveGraphs
(SocialNetworks)
Ch10:AnalysisofSocialNetworks
13
(11/16)
14
(11/23)
WebAdvertising
Ch8:AdvertisingontheWeb
Ch4:Miningdatastreams
8
(10/12)
Miningdatastreams
Readings
Ch1:DataMiningand
Ch2:Large-ScaleFileSystemsand
Map-Reduce
Ch2:Large-ScaleFileSystemsand
Map-Reduce
Ch6:Frequentitemsets,
Ch3:FindingSimilarItems(section
3.5:DistanceMeasures)
Ch6:Frequentitemsets
Homework
Instructor
Wu
Wu
Homework1
assigned
Chiang
Chiang
Ch3:FindingSimilarItems
Homework1
Wu
due,Homework
2assigned
Wu
Ch9:Recommendationsystems,
additionalreadings
Chiang
Ch9:Recommendationsystems
Homework2
due,
Homework3
assigned
Chiang
Homework3
due,
Homework4
assigned
Wu
Ch10:AnalysisofSocialNetworks
Wu
Chiang
Homework4
Chiang
due,Homework
5assigned
Wu
Homework5
due
Wu
15
(11/30)
Final(TBD12/912/11)
Miningdatastreams
CourseSummary
FinalExam
Chiang/Wu
StatementonAcademicConductandSupportSystems
AcademicConduct
Plagiarism–presentingsomeoneelse’sideasasyourown,eitherverbatimorrecastinyourown
words–isaseriousacademicoffensewithseriousconsequences.Pleasefamiliarizeyourselfwith
thediscussionofplagiarisminSCampusinSection11,BehaviorViolatingUniversityStandards
https://scampus.usc.edu/1100-behavior-violating-university-standards-and-appropriatesanctions.Otherformsofacademicdishonestyareequallyunacceptable.Seeadditional
informationinSCampusanduniversitypoliciesonscientificmisconduct,
http://policy.usc.edu/scientific-misconduct.
Discrimination,sexualassault,andharassmentarenottoleratedbytheuniversity.Youare
encouragedtoreportanyincidentstotheOfficeofEquityandDiversityhttp://equity.usc.eduorto
theDepartmentofPublicSafetyhttp://capsnet.usc.edu/department/department-publicsafety/online-forms/contact-us.ThisisimportantforthesafetyofthewholeUSC
community.Anothermemberoftheuniversitycommunity–suchasafriend,classmate,advisor,
orfacultymember–canhelpinitiatethereport,orcaninitiatethereportonbehalfofanother
person.TheCenterforWomenandMenhttp://www.usc.edu/student-affairs/cwm/provides24/7
confidentialsupport,andthesexualassaultresourcecenterwebpagehttp://sarc.usc.edudescribes
reportingoptionsandotherresources.
SupportSystems
AnumberofUSC’sschoolsprovidesupportforstudentswhoneedhelpwithscholarly
writing.Checkwithyouradvisororprogramstafftofindoutmore.Studentswhoseprimary
languageisnotEnglishshouldcheckwiththeAmericanLanguageInstitute
http://dornsife.usc.edu/ali,whichsponsorscoursesandworkshopsspecificallyforinternational
graduatestudents.TheOfficeofDisabilityServicesandPrograms
http://sait.usc.edu/academicsupport/centerprograms/dsp/home_index.htmlprovidescertification
forstudentswithdisabilitiesandhelpsarrangetherelevantaccommodations.Ifan
officiallydeclaredemergencymakestraveltocampusinfeasible,USCEmergencyInformation
http://emergency.usc.eduwillprovidesafetyandotherupdates,includingwaysinwhich
instructionwillbecontinuedbymeansofblackboard,teleconferencing,andothertechnology.