public Product RecommendProductItemBased(Order order, ISimilarityCalculable calculable, int kNearest)
{
var itemData = GetItemData();
var currentPurchase = ConvertToPurchaseData(order);
for (int i = 0; i < itemData.Count; i++)
{
var data1 = itemData[i];
for (int j = 0; j < itemData.Count; j++)
{
var similarity = new ItemSimilarity();
similarity.ProductId = itemData[j].ProductId;
var data2 = itemData[j];
if (j != i)
{
similarity.Similarity = calculable.CalculateSimilarity(data1.PurchasedByCustomer, data2.PurchasedByCustomer);
}
data1.SimilarityVector.Add(similarity);
}
}
var result = FindRecommendationItemBased(itemData, currentPurchase, kNearest);
if (result == -1)
{
return(null);
}
return(_products.ToList().SingleOrDefault(x => x.ProductId == result));
}
public Product RecommendProductUserBased(Order order, ISimilarityCalculable calculable, int kNearest)
{
var purchaseData = GetPurchaseData();
var data1 = ConvertToPurchaseData(order);
foreach (var data2 in purchaseData)
{
if (data1.OrderID != data2.OrderID)
{
data2.Similarity = calculable.CalculateSimilarity(data1.Data, data2.Data);
}
}
var result = FindRecommendationUserBased(purchaseData, data1, kNearest);
if (result == -1)
{
return(null);
}
return(_products.ToList().SingleOrDefault(x => x.ProductId == result));
}
