文件名称:recommender-
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Collaborative Filtering，基于Collaborative Filtering，建立主动为用户推荐商品的推荐系统。实现参考协同过滤算法或它的优化，实现并改进算法，计算出每个客户对未购买的商品的兴趣度，并向客户主动推荐他最感兴趣的N个商品。实验数据可以从MovieLens.com下载。要求使用至少10，000不同用户的数据，至少1000个不同的movie。-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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下载文件列表
recommender
...........\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