public Dictionary <int, double> PerformBP(BeliefPropagation BP, int target_user, double target_prior)
{
List <Score> belief_score_list = new List <Score>();
BP.AssignNodePotential(target_user, target_prior);
for (int iter = 0; iter < num_iter; iter++)
{
// message passing
BP.PassMessage(target_user, iter);
belief_score_list = BP.ComputeBeliefScore(target_user, test_items, num_recommend, correct_user_item);
}
Dictionary <int, double> recommend_items = new Dictionary <int, double>();
for (int i = 0; i < belief_score_list.Count; i++)
{
recommend_items.Add(belief_score_list[i].item_id, belief_score_list[i].score);
}
return(recommend_items);
}
public override void Recommend()
{
BeliefPropagation BP_like = new BeliefPropagation(like_edges, node_potential_like, propagation_matrix, max_user_id, max_item_id);
BeliefPropagation BP_dislike = new BeliefPropagation(dislike_edges, node_potential_dislike, propagation_matrix, max_user_id, max_item_id);
recommend_user_item = new Dictionary <int, List <Score> >();
int num = 0;
foreach (int target_user in correct_user_item.Keys)
{
if (!node_potential_like.ContainsKey(target_user) && !node_potential_dislike.ContainsKey(target_user))
{
continue;
}
if (num != 0)
{
like_edges.Clear();
dislike_edges.Clear();
}
Dictionary <int, double> like_items = PerformBP(BP_like, target_user, 0.9);
Dictionary <int, double> dislike_items = PerformBP(BP_dislike, target_user, 0.7);
double dislike_min = 1d;
foreach (int item_id in dislike_items.Keys)
{
if (dislike_items[item_id] == 0)
{
continue;
}
if (dislike_min > dislike_items[item_id])
{
dislike_min = dislike_items[item_id];
}
}
List <Score> recommend_items = new List <Score>();
foreach (int item_id in like_items.Keys)
{
double final = 0d;
if (candidate_item == "Longtail_items")
{
if (Program.tophead_items.Contains(item_id))
{
continue;
}
}
if (node_potential_like[target_user].linkednode_list.Contains(item_id))
{
continue;
}
else if (node_potential_dislike.ContainsKey(target_user))
{
if (node_potential_dislike[target_user].linkednode_list.Contains(item_id))
{
continue;
}
}
if (like_items[item_id] == 0)
{
continue;
}
if (dislike_items[item_id] == 0)
{
final = like_items[item_id] - dislike_min;
}
else
{
final = like_items[item_id] - dislike_items[item_id];
}
Score user_score = new Score(item_id, final);
recommend_items.Add(user_score);
}
recommend_items.Sort(Score.CompareScore);
recommend_user_item.Add(target_user, recommend_items);
num++;
if (num % 50 == 0)
{
Console.WriteLine("Compute BP score for {0} user / {1} users (fold{2}): Complete", num, correct_user_item.Count(), fold);
}
}
Console.WriteLine("Compute BP scores: Complete");
}