// Написать getTopNRecommendations


        public static List <PredictedItemRating> getTopNRecommendations(List <PredictedItemRating> recommendations, int topN)
        {
            PredictedItemRating.sort(recommendations);

            List <PredictedItemRating> topRecommendations = new List <PredictedItemRating>();

            recommendations.ForEach(delegate(PredictedItemRating r)
            {
                if (topRecommendations.Count >= topN)
                {
                    return;
                }

                topRecommendations.Add(r);
            });

            return(topRecommendations);
        }
예제 #2
0
        public List <PredictedItemRating> recommend(BookUser user, int topN)
        {
            List <PredictedItemRating> recommendations = new List <PredictedItemRating>();

            double maxRating = -1.0d;

            for (int i = 0; i < dataSet.getBooks().Count; i++)
            {
                if (!skipItem(user, dataSet.getBooks()[i]))
                {
                    double predictedRating = predictRating(user, dataSet.getBooks()[i]);
                    if (maxRating < predictedRating)
                    {
                        maxRating = predictedRating;
                    }

                    if (!Double.IsNaN(predictedRating))
                    {
                        recommendations.Add(new PredictedItemRating(user.UserId, dataSet.getBooks()[i].getId(), predictedRating));
                    }
                }
                else
                {
                    if (verbose)
                    {
                        Console.WriteLine("Skipping item: " + dataSet.getBooks()[i].getName());
                    }
                }
            }

            this.maxPredictedRating.Add(user.UserId, maxRating);

            List <PredictedItemRating> topNRecommendations = PredictedItemRating.getTopNRecommendations(recommendations, topN);

            if (verbose)
            {
                PredictedItemRating.printUserRecommendations(user, dataSet, topNRecommendations);
            }

            return(topNRecommendations);
        }