public void TestHowMany()
{
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", 0.1, 0.4, 0.5, 0.8, 0.9, 1.0));
users.Add(GetUser("test5", 0.2, 0.3, 0.6, 0.7, 0.1, 0.2));
DataModel dataModel = new GenericDataModel(users);
IList<GenericItemCorrelation.ItemItemCorrelation> correlations =
new List<GenericItemCorrelation.ItemItemCorrelation>(6);
for (int i = 0; i < 6; i++)
{
for (int j = i + 1; j < 6; j++)
{
correlations.Add(
new GenericItemCorrelation.ItemItemCorrelation(new GenericItem<String>(i.ToString()),
new GenericItem<String>(j.ToString()),
1.0 / (1.0 + (double)i + (double)j)));
}
}
ItemCorrelation correlation = new GenericItemCorrelation(correlations);
Recommender recommender = new GenericItemBasedRecommender(dataModel, correlation);
IList<RecommendedItem> fewRecommended = recommender.Recommend("test1", 2);
IList<RecommendedItem> moreRecommended = recommender.Recommend("test1", 4);
for (int i = 0; i < fewRecommended.Count; i++)
{
Assert.AreEqual(fewRecommended[i].Item, moreRecommended[i].Item);
}
}
public void TestRescorer()
{
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));
DataModel dataModel = new GenericDataModel(users);
Item item1 = new GenericItem<String>("0");
Item item2 = new GenericItem<String>("1");
Item item3 = new GenericItem<String>("2");
Item item4 = new GenericItem<String>("3");
ICollection<GenericItemCorrelation.ItemItemCorrelation> correlations =
new List<GenericItemCorrelation.ItemItemCorrelation>(6);
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item2, 1.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item3, 0.5));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item4, 0.2));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item2, item3, 0.7));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item2, item4, 0.5));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item3, item4, 0.9));
ItemCorrelation correlation = new GenericItemCorrelation(correlations);
Recommender recommender = new GenericItemBasedRecommender(dataModel, correlation);
IList<RecommendedItem> originalRecommended = recommender.Recommend("test1", 2);
IList<RecommendedItem> rescoredRecommended =
recommender.Recommend("test1", 2, new ReversingRescorer<Item>());
Assert.IsNotNull(originalRecommended);
Assert.IsNotNull(rescoredRecommended);
Assert.AreEqual(2, originalRecommended.Count);
Assert.AreEqual(2, rescoredRecommended.Count);
Assert.AreEqual(originalRecommended[0].Item, rescoredRecommended[1].Item);
Assert.AreEqual(originalRecommended[1].Item, rescoredRecommended[0].Item);
}
private static ItemBasedRecommender buildRecommender2()
{
List<User> users = new List<User>(4);
users.Add(GetUser("test1", 0.1, 0.3, 0.9, 0.8));
users.Add(GetUser("test2", 0.2, 0.3, 0.3, 0.4));
users.Add(GetUser("test3", 0.4, 0.3, 0.5, 0.1, 0.1));
users.Add(GetUser("test4", 0.7, 0.3, 0.8, 0.5, 0.6));
DataModel dataModel = new GenericDataModel(users);
ICollection<GenericItemCorrelation.ItemItemCorrelation> correlations =
new List<GenericItemCorrelation.ItemItemCorrelation>(10);
Item item1 = new GenericItem<String>("0");
Item item2 = new GenericItem<String>("1");
Item item3 = new GenericItem<String>("2");
Item item4 = new GenericItem<String>("3");
Item item5 = new GenericItem<String>("4");
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item2, 1.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item3, 0.8));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item4, -0.6));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item5, 1.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item2, item3, 0.9));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item2, item4, 0.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item2, item2, 1.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item3, item4, -0.1));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item3, item5, 0.1));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item4, item5, -0.5));
ItemCorrelation correlation = new GenericItemCorrelation(correlations);
return new GenericItemBasedRecommender(dataModel, correlation);
}
private static ItemBasedRecommender buildRecommender()
{
DataModel dataModel = new GenericDataModel(GetMockUsers());
ICollection<GenericItemCorrelation.ItemItemCorrelation> correlations =
new List<GenericItemCorrelation.ItemItemCorrelation>(2);
Item item1 = new GenericItem<String>("0");
Item item2 = new GenericItem<String>("1");
Item item3 = new GenericItem<String>("2");
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item2, 1.0));
correlations.Add(new GenericItemCorrelation.ItemItemCorrelation(item1, item3, 0.5));
ItemCorrelation correlation = new GenericItemCorrelation(correlations);
return new GenericItemBasedRecommender(dataModel, correlation);
}
