public void testCorrelation()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2, 3, 4, 5 },
new Double?[][] {
new double?[] { 1.0, 1.0 },
new double?[] { 1.0, null, 1.0 },
new double?[] { null, null, 1.0, 1.0, 1.0 },
new double?[] { 1.0, 1.0, 1.0, 1.0, 1.0 },
new double?[] { null, 1.0, 1.0, 1.0, 1.0 },
});
LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(dataModel);
assertCorrelationEquals(0.12160727029227925, similarity.ItemSimilarity(1, 0));
assertCorrelationEquals(0.12160727029227925, similarity.ItemSimilarity(0, 1));
assertCorrelationEquals(0.5423213660693732, similarity.ItemSimilarity(1, 2));
assertCorrelationEquals(0.5423213660693732, similarity.ItemSimilarity(2, 1));
assertCorrelationEquals(0.6905400104897509, similarity.ItemSimilarity(2, 3));
assertCorrelationEquals(0.6905400104897509, similarity.ItemSimilarity(3, 2));
assertCorrelationEquals(0.8706358464330881, similarity.ItemSimilarity(3, 4));
assertCorrelationEquals(0.8706358464330881, similarity.ItemSimilarity(4, 3));
}
public void testCorrelation()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2, 3, 4, 5},
new Double?[][] {
new double?[]{1.0, 1.0},
new double?[]{1.0, null, 1.0},
new double?[]{null, null, 1.0, 1.0, 1.0},
new double?[]{1.0, 1.0, 1.0, 1.0, 1.0},
new double?[]{null, 1.0, 1.0, 1.0, 1.0},
});
LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(dataModel);
assertCorrelationEquals(0.12160727029227925, similarity.ItemSimilarity(1, 0));
assertCorrelationEquals(0.12160727029227925, similarity.ItemSimilarity(0, 1));
assertCorrelationEquals(0.5423213660693732, similarity.ItemSimilarity(1, 2));
assertCorrelationEquals(0.5423213660693732, similarity.ItemSimilarity(2, 1));
assertCorrelationEquals(0.6905400104897509, similarity.ItemSimilarity(2, 3));
assertCorrelationEquals(0.6905400104897509, similarity.ItemSimilarity(3, 2));
assertCorrelationEquals(0.8706358464330881, similarity.ItemSimilarity(3, 4));
assertCorrelationEquals(0.8706358464330881, similarity.ItemSimilarity(4, 3));
}
public ActionResult Recommend(string filmIdsJson)
{
var filmIds = (new JavaScriptSerializer()).Deserialize<long[]>(filmIdsJson);
var pathToDataFile =
Path.Combine(System.Web.HttpRuntime.AppDomainAppPath, "data/albums.dat");
if (dataModel == null) {
try
{
dataModel = new FileDataModel(pathToDataFile, false, FileDataModel.DEFAULT_MIN_RELOAD_INTERVAL_MS, false);
}
catch (Exception e)
{
var exe = e.ToString();
}
}
var plusAnonymModel = new PlusAnonymousUserDataModel(dataModel);
var prefArr = new GenericUserPreferenceArray(filmIds.Length);
prefArr.SetUserID(0, PlusAnonymousUserDataModel.TEMP_USER_ID);
for (int i = 0; i < filmIds.Length; i++) {
prefArr.SetItemID(i, filmIds[i]);
prefArr.SetValue(i, 5); // lets assume max rating
}
plusAnonymModel.SetTempPrefs(prefArr);
var similarity = new LogLikelihoodSimilarity(plusAnonymModel);
var neighborhood = new NearestNUserNeighborhood(15, similarity, plusAnonymModel);
var recommender = new GenericBooleanPrefUserBasedRecommender(plusAnonymModel, neighborhood, similarity);
var recommendedItems = recommender.Recommend(PlusAnonymousUserDataModel.TEMP_USER_ID, 5, null);
return Json( recommendedItems.Select(ri => new Dictionary<string, object>() {
{"id", ri.GetItemID() },
{"rating", ri.GetValue() },
}).ToArray() );
}
public void testNoSimilarity()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2, 3, 4 },
new Double?[][] {
new double?[] { 1.0, null, 1.0, 1.0 },
new double?[] { 1.0, null, 1.0, 1.0 },
new double?[] { null, 1.0, 1.0, 1.0 },
new double?[] { null, 1.0, 1.0, 1.0 },
});
LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(dataModel);
assertCorrelationEquals(Double.NaN, similarity.ItemSimilarity(1, 0));
assertCorrelationEquals(Double.NaN, similarity.ItemSimilarity(0, 1));
assertCorrelationEquals(0.0, similarity.ItemSimilarity(2, 3));
assertCorrelationEquals(0.0, similarity.ItemSimilarity(3, 2));
}
public void testNoSimilarity()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2, 3, 4},
new Double?[][] {
new double?[]{1.0, null, 1.0, 1.0},
new double?[]{1.0, null, 1.0, 1.0},
new double?[]{null, 1.0, 1.0, 1.0},
new double?[]{null, 1.0, 1.0, 1.0},
});
LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(dataModel);
assertCorrelationEquals(Double.NaN, similarity.ItemSimilarity(1, 0));
assertCorrelationEquals(Double.NaN, similarity.ItemSimilarity(0, 1));
assertCorrelationEquals(0.0, similarity.ItemSimilarity(2, 3));
assertCorrelationEquals(0.0, similarity.ItemSimilarity(3, 2));
}