为豆瓣电影实现Item-based协同过滤的推荐系统

     
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public class DoubanItemBasedRecommender {
     
    public static void main(String[] args) throws Exception {
     
        String base = args[0];
     
        File file = new File(base + "user_movies.csv");
     
        DoubanFileDataModel model = new DoubanFileDataModel(file);
     
        ItemSimilarity similarity = new PearsonCorrelationSimilarity(model);
     
        ItemBasedRecommender recommender = new GenericItemBasedRecommender(model, similarity);
     
        BatchItemSimilarities batch = new MultithreadedBatchItemSimilarities(recommender, 5);
     
        int numSimilarities = batch.computeItemSimilarities(Runtime.getRuntime().availableProcessors(), 1, new FileSimilarItemsWriter(new File(base + "item_result.csv")));
     
        System.out.println("Computed " + numSimilarities + " similarities for " + model.getNumItems() + " items " + "and saved them to file " + base + "item_result.csv");
     
    }
     
}

     
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......
     
25821461,26253733,0.8279288411140442
     
25821461,26252196,0.819756031036377
     
25821461,26366634,0.8181818127632141
     
25821461,25919385,0.7033082246780396
     
25821585,26328118,0.794719398021698
     
25821585,22556810,0.7655318379402161
     
25821585,1972724,0.6770924925804138
     
25821585,25809260,0.6347297430038452
     
......