private List <UserProductRatings> GetNearestNeighbors(UserProductRatings user, int numUsers)
{
List <UserProductRatings> neighbors = new List <UserProductRatings>();
for (int i = 0; i < ratings.Users.Count; i++)
{
if (ratings.Users[i].UserID == user.UserID)
{
ratings.Users[i].Score = double.NegativeInfinity;
}
else
{
ratings.Users[i].Score = comparer.CompareVectors(ratings.Users[i].ProductRatings, user.ProductRatings);
}
}
var similarUsers = ratings.Users.OrderByDescending(x => x.Score);
return(similarUsers.Take(numUsers).ToList());
}
public List <Suggestion> GetSuggestions(ObjectId userId, int numSuggestions)
{
int userIndex = ratings.UserIndexToID.IndexOf(userId);
UserProductRatings user = ratings.Users[userIndex];
List <Suggestion> suggestions = new List <Suggestion>();
var neighbors = GetNearestNeighbors(user, neighborCount);
for (int productIndex = 0; productIndex < ratings.ProductIndexToID.Count; productIndex++)
{
// If the user in question hasn't rated the given product yet
if (user.ProductRatings[productIndex] == 0)
{
double score = 0.0;
int count = 0;
for (int u = 0; u < neighbors.Count; u++)
{
if (neighbors[u].ProductRatings[productIndex] != 0)
{
// Calculate the weighted score for this product
score += neighbors[u].ProductRatings[productIndex];
count++;
}
}
if (count > 0)
{
score /= count;
}
suggestions.Add(new Suggestion(userId, ratings.ProductIndexToID[productIndex], score));
}
}
suggestions.Sort((c, n) => n.Rating.CompareTo(c.Rating));
return(suggestions.Take(numSuggestions).ToList());
}
