public static List <int> RecommendSpreadingActivation(int bookId,
SimilarityCacheModels simCacheModel, string userId = null, int howMany = 6)
{
var sw = Stopwatch.StartNew();
RecommenderSpreadingActivation recommender = new RecommenderSpreadingActivation(2, 500, 50, simCacheModel);
List <int> result = recommender.Recommend(bookId, userId, howMany);
System.Console.WriteLine($"Spreading recommendation took: {sw.ElapsedMilliseconds}ms");
return(result);
}
private static void TestRecSpreadingActivation(List <int> bookIds, int maxLevel,
int numberOfNSimilarNeighbors, int numberOfNeighborsForNextLevel)
{
List <Recommendation> recommendationsRSA = new List <Recommendation>();
String commentRDEBS = "userId=null, maxLevel=" + maxLevel + ", numberOfSimilarNeighbors=" + numberOfNSimilarNeighbors + ", numberOfNeighborsForNextLevel=" + numberOfNeighborsForNextLevel + ", backSpreading=yes";
BookRecommenderContext db = new BookRecommenderContext();
SpreadingRecommenderCache model = new SpreadingRecommenderCache();
model.Initialize(db);
foreach (int bookIdI in bookIds)
{
RecommenderSpreadingActivation recommender = new RecommenderSpreadingActivation(
maxLevel, numberOfNSimilarNeighbors, numberOfNeighborsForNextLevel, new SimilarityCacheModels(model));
List <int> recommendationListI = recommender.Recommend(bookIdI, null, HOW_MANY_REC);
Recommendation recommendationI = new Recommendation(bookIdI, recommendationListI);
recommendationsRSA.Add(recommendationI);
System.Console.WriteLine(recommendationI.exportAsString());
}
String fileName = "RecommenderSpreadingActivationLevel" + maxLevel + "SimilarNeighbors" + numberOfNSimilarNeighbors + "NeighborsForNextLevel" + numberOfNeighborsForNextLevel + ".rec";
ExportsRecommendationsToFile(recommendationsRSA, commentRDEBS, fileName);
}
