Mahout - How to read a custom input file?

Question

I follow this topic and use MemoryIDMigrator to get a long ID for my products : Mahout : To read a custom input file

But I can't initialize IDMigrator like this because the parent constructor need to come first :

public MemoryIDMigrator memoryIDMigrator;

public CustomFileDataModel(File dataFile) throws IOException {

    this.memoryIDMigrator = new MemoryIDMigrator();
    super(dataFile);
}

@Override
protected long readItemIDFromString(String stringID) {

    long result = this.memoryIDMigrator.toLongID(stringID);
    this.memoryIDMigrator.storeMapping(result, stringID);
    return result;
}

How could I give this parameter to get back my String ID ? I need something like this :

    List<RecommendedItem> recommendations = recommender.recommend(2, 5);
    for (RecommendedItem recommendation : recommendations) {
        System.out.println(memoryIDMigrator.toStringID(recommendation.getItemID());
    }

Answer 1

I just found a solution ! In my opinion it's not the best way to do it but it works.

When my override function try to read an item, I prevent the creation of a new map if it had already been created :

public class CustomFileDataModel extends FileDataModel {

    public MemoryIDMigrator memoryIDMigrator;
    private boolean loaded;

    public CustomFileDataModel(File dataFile) throws IOException {
        super(dataFile);
    }

    @Override
    protected long readItemIDFromString(String stringID) {
        if (!this.loaded) {
            this.memoryIDMigrator = new MemoryIDMigrator();
            this.loaded = true;
        }
        long result = this.memoryIDMigrator.toLongID(stringID);
        this.memoryIDMigrator.storeMapping(result, stringID);
        return result;
    }
}

Similarly, if you want to use a custom user ID, you can override the readUserIDFromString() function.

And then to recover my string ID, I proceed like this :

public static void main( String[] args ) throws IOException, TasteException {

    CustomFileDataModel model = new CustomFileDataModel(new File("path/to/data.csv"));

    UserSimilarity similarity = new PearsonCorrelationSimilarity(model);

    UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);

    UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);

    List<RecommendedItem> recommendations = recommender.recommend(2, 5);
    for (RecommendedItem recommendation : recommendations) {
        System.out.println(model.memoryIDMigrator.toStringID(recommendation.getItemID()));
    }
}