static void KnnItemBasedRecommenderTest()
{
Console.WriteLine("KnnItemBasedRecommenderTest");
System.Diagnostics.Stopwatch watch = new System.Diagnostics.Stopwatch();
watch.Start();
var model = new FileDataModel(filePath);
ItemSimilarity similarity = new LogLikelihoodSimilarity(model);
Optimizer optimizer = new ConjugateGradientOptimizer();
var recommender = new KnnItemBasedRecommender(model, similarity, optimizer, 10);
var iter = model.getUserIDs();
while (iter.MoveNext())
{
var userId = iter.Current;
var recommendedItems = recommender.recommend(userId, 5);
Console.Write("uid:" + userId);
foreach (var ritem in recommendedItems)
{
Console.Write("(" + ritem.getItemID() + "," + ritem.getValue() + ")");
}
Console.WriteLine();
}
watch.Stop();
Console.WriteLine(watch.ElapsedMilliseconds);
}
static void GenericUserBasedRecommenderTest()
{
Console.WriteLine("GenericUserBasedRecommenderTest");
System.Diagnostics.Stopwatch watch = new System.Diagnostics.Stopwatch();
watch.Start();
var model = new FileDataModel(filePath);
var similarity = new PearsonCorrelationSimilarity(model);
var neighborhood = new NearestNUserNeighborhood(4, similarity, model);
var recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
var iter = model.getUserIDs();
while (iter.MoveNext())
{
var userId = iter.Current;
var recommendedItems = recommender.recommend(userId, 5);
Console.Write("uid:" + userId);
foreach (var ritem in recommendedItems)
{
Console.Write("(" + ritem.getItemID() + "," + ritem.getValue() + ")");
}
Console.WriteLine();
}
watch.Stop();
Console.WriteLine(watch.ElapsedMilliseconds);
}
static void GenericItemBasedRecommenderTestByTanimotoCoefficientSimilarity()
{
Console.WriteLine("GenericItemBasedRecommenderTestByTanimotoCoefficientSimilarity");
System.Diagnostics.Stopwatch watch = new System.Diagnostics.Stopwatch();
watch.Start();
var model = new FileDataModel(filePath);
ItemSimilarity similarity = new TanimotoCoefficientSimilarity(model);
var recommender = new GenericItemBasedRecommender(model, similarity);
var iter = model.getUserIDs();
while (iter.MoveNext())
{
var userId = iter.Current;
var recommendedItems = recommender.recommend(userId, 5);
Console.Write("uid:" + userId);
foreach (var ritem in recommendedItems)
{
Console.Write("(" + ritem.getItemID() + "," + ritem.getValue() + ")");
}
Console.WriteLine();
}
watch.Stop();
Console.WriteLine(watch.ElapsedMilliseconds);
}
static void SlopeOneRecommenderTest()
{
Console.WriteLine("SlopeOneRecommenderTest");
var model = new FileDataModel(filePath);
var recommender = new SlopeOneRecommender(model);
var ids = model.getUserIDs();
while (ids.MoveNext())
{
var userId = ids.Current;
var recommendedItems = recommender.recommend(userId, 5);
Console.Write("uid:" + userId);
foreach (var ritem in recommendedItems)
{
Console.Write("(" + ritem.getItemID() + "," + ritem.getValue() + ")");
}
Console.WriteLine();
}
}