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Recommended Systems Resource Center

 

Recommender Systems Course Syllabi
Stanford University CS345 Syllabus
http://www.stanford.edu/class/cs345a/
Stanford University CS345 Syllabus. "Data Mining," covers an introduction to web mining, association rules, page rank, topic-specific page rank, hits and spam, minhashing, locality-sensitive hashing, clustering, recommender systems, structured data extraction, virtual databases, online algorithms, search advertising and stream mining.
DePaul University Syllabus
http://maya.cs.depaul.edu/~classes/ds575/project.html
DePaul University's syllabus for their course "Intelligent Information Retrieval." This course covers personalized search, relevance feedback, client-side and server-side agents for filtering information, web content mining, collaborative filtering and recommend er systems, and the use of clustering. Projects include building a search/retrieval system, building a web search engine, implementing a simple meta-search engine, implementation a web browsing assistant using clustering, designing a domain-specific search agent, implementing a web mail, news or web filtering system, design and enhance a user interface for a retrieval system, using HTML parsing, and building a simple recommend er system.
University of Michigan Syllabus
http://www.si.umich.edu/~presnick/courses/fall06/recommender_systems.htm
Syllabus for a seven-week Recommender Systems course at the University of Michigan. Topics include an introduction (the design space), algorithms (person-person, item-item, matrix methods and graph methods), anonymity and privacy, prediction evaluation methods, rating scales, implicit ratings, herding and deliberate manipulation, use of ratings and social fragmentation.

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Update :: December 18, 2017