private PurchaseData ConvertToPurchaseData(Order order)
{
var orderDetails = _orderDetails.Where(o => o.OrderId == order.OrderId).ToList();
PurchaseData data = new PurchaseData();
data.OrderID = order.OrderId;
data.Data = new int[_products.Count];
for (int i = 0; i < PurchaseData.ProductIDs.Length; i++)
{
foreach (var orderDetail in orderDetails)
{
if (orderDetail.ProductId == PurchaseData.ProductIDs[i])
{
data.Data[i] = 1;
break;
}
}
}
return(data);
}
private int FindRecommendationUserBased(List <PurchaseData> purchaseData, PurchaseData p, int kNearest)
{
List <PurchaseData> purchases;
// Use k-nearest if possible
if (purchaseData.Count >= kNearest)
{
purchases = purchaseData.OrderByDescending(purchase => purchase.Similarity).ToList().GetRange(0, kNearest);
}
// else as many as possible
else
{
purchases = purchaseData.OrderByDescending(purchase => purchase.Similarity).ToList();
}
// Calculate similarity
double similaritySum = purchases.Sum(purchase => purchase.Similarity);
foreach (var purchase in purchases)
{
purchase.Influence = purchase.Similarity / similaritySum;
}
// Sum weighted similarity for each product
var recommendations = new Dictionary <int, double>();
var chosenInStore = _recommendationResults;
foreach (PurchaseData purchase in purchases)
{
foreach (var recommendationResult in chosenInStore.Where(r => r.OrderId == purchase.OrderID))
{
if (recommendations.ContainsKey(recommendationResult.SelectedProductId))
{
recommendations[recommendationResult.SelectedProductId] += purchase.Influence;
}
else
{
recommendations.Add(recommendationResult.SelectedProductId, purchase.Influence);
}
}
}
var sortedRecommendations = recommendations.OrderByDescending(product => product.Value).ToList();
int recommendedProduct = -1;
// TODO: Make this look if similarity is 0 instead
if (sortedRecommendations.Count == 0)
{
Random random = new Random();
var instoreProducts = _products.Where(x => x.IsInStore).ToList();
recommendedProduct = instoreProducts[random.Next(instoreProducts.Count)].ProductId;
LogResult("UserBased", kNearest, p.OrderID, recommendedProduct, true, sortedRecommendations);
return(recommendedProduct);
}
LogResult("UserBased", kNearest, p.OrderID, sortedRecommendations[0].Key, false, sortedRecommendations);
recommendedProduct = sortedRecommendations[0].Key;
return(recommendedProduct);
}
