public void TestIsolatedUser()
{
List <User> users = new List <User>(3);
users.Add(GetUser("test1", 0.1, 0.2));
users.Add(GetUser("test2", 0.2, 0.3, 0.3, 0.6));
users.Add(GetUser("test3", 0.4, 0.4, 0.5, 0.9));
users.Add(GetUser("test4"));
DataModel dataModel = new GenericDataModel(users);
UserCorrelation correlation = new PearsonCorrelation(dataModel);
UserNeighborhood neighborhood = new NearestNUserNeighborhood(3, correlation, dataModel);
UserBasedRecommender recommender = new GenericUserBasedRecommender(dataModel, neighborhood, correlation);
ICollection <User> mostSimilar = recommender.MostSimilarUsers("test4", 3);
Assert.IsNotNull(mostSimilar);
Assert.AreEqual(0, mostSimilar.Count);
}
public void TestIsolatedUser()
{
List<User> users = new List<User>(3);
users.Add(GetUser("test1", 0.1, 0.2));
users.Add(GetUser("test2", 0.2, 0.3, 0.3, 0.6));
users.Add(GetUser("test3", 0.4, 0.4, 0.5, 0.9));
users.Add(GetUser("test4"));
DataModel dataModel = new GenericDataModel(users);
UserCorrelation correlation = new PearsonCorrelation(dataModel);
UserNeighborhood neighborhood = new NearestNUserNeighborhood(3, correlation, dataModel);
UserBasedRecommender recommender = new GenericUserBasedRecommender(dataModel, neighborhood, correlation);
ICollection<User> mostSimilar = recommender.MostSimilarUsers("test4", 3);
Assert.IsNotNull(mostSimilar);
Assert.AreEqual(0, mostSimilar.Count);
}
