Description: Collaborative Filtering，Based Collaborative Filtering, the initiative for the establishment of user recommended product recommendation system. Reference implementation or its collaborative filtering algorithm optimized to achieve and improve the algorithm to calculate each customer not purchased the degree of interest to the customer the initiative to recommend N of products he is most interested. Experimental data can be downloaded MovieLens.com. It requires the use of at least 10,000 different user data, at least 1,000 different movie.
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...........\calculate.cpp
...........\calculate.o
...........\category.dat
...........\config.cpp
...........\config.h
...........\config.o
...........\dataReader.cpp
...........\dataReader.h
...........\dataReader.o
...........\dataStructure.cpp
...........\dataStructure.h
...........\dataStructure.o
...........\frCal.cpp
...........\frCal.h
...........\frCal.o
...........\IniFile.cpp
...........\IniFile.h
...........\IniFile.o
...........\kmeans.cpp
...........\kmeans.h
...........\kmeans.o
...........\mae.cpp
...........\mae.h
...........\mae.o
...........\main.cpp
...........\main.o
...........\Makefile
...........\movies.dat
...........\out.csv
...........\ra.test
...........\ra.train
...........\ratings.dat
...........\recommend
...........\recommender.cpp
...........\recommender.h
...........\recommender.o
...........\run.sh
...........\score.csv
...........\sim.csv
...........\simCalculate.cpp
...........\simCalculate.h
...........\simCalculate.o
...........\sys.cfg
...........\type.h
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