C#实现协同过滤算法的实例代码

using system;
using system.collections.generic;
using system.linq;
using system.text;
namespace slopeone
{
    public class rating
    {
        public float value { get; set; }
        public int freq { get; set; }
        public float averagevalue
        {
            get { return value / freq; }
        }
    }
    public class ratingdifferencecollection : dictionary<string, rating>
    {
        private string getkey(int item1id, int item2id)
        {
            return (item1id < item2id) ? item1id + "/" + item2id : item2id + "/" + item1id ;
        }
        public bool contains(int item1id, int item2id)
        {
            return this.keys.contains<string>(getkey(item1id, item2id));
        }
        public rating this[int item1id, int item2id]
        {
            get {
                    return this[this.getkey(item1id, item2id)];
            }
            set { this[this.getkey(item1id, item2id)] = value; }
        }
    }
     public class slopeone
    {       
        public ratingdifferencecollection _diffmarix = new ratingdifferencecollection();  // the dictionary to keep the diff matrix
        public hashset<int> _items = new hashset<int>();  // tracking how many items totally
        public void adduserratings(idictionary<int, float> userratings)
        {
            foreach (var item1 in userratings)
            {
                int item1id = item1.key;
                float item1rating = item1.value;
                _items.add(item1.key);
                foreach (var item2 in userratings)
                {
                    if (item2.key <= item1id) continue; // eliminate redundancy
                    int item2id = item2.key;
                    float item2rating = item2.value;
                    rating ratingdiff;
                    if (_diffmarix.contains(item1id, item2id))
                    {
                        ratingdiff = _diffmarix[item1id, item2id];
                    }
                    else
                    {
                        ratingdiff = new rating();
                        _diffmarix[item1id, item2id] = ratingdiff;
                    }
                    ratingdiff.value += item1rating - item2rating;
                    ratingdiff.freq += 1;
                }
            }
        }
        // input ratings of all users
        public void adduerratings(ilist<idictionary<int, float>> ratings)
        {
            foreach(var userratings in ratings)
            {
                adduserratings(userratings);
            }
        }
        public idictionary<int, float> predict(idictionary<int, float> userratings)
        {
            dictionary<int, float> predictions = new dictionary<int, float>();
            foreach (var itemid in this._items)
            {
                if (userratings.keys.contains(itemid))    continue; // user has rated this item, just skip it
                rating itemrating = new rating();
                foreach (var userrating in userratings)
                {
                    if (userrating.key == itemid) continue;
                    int inputitemid = userrating.key;
                    if (_diffmarix.contains(itemid, inputitemid))
                    {
                        rating diff = _diffmarix[itemid, inputitemid];
                        itemrating.value += diff.freq * (userrating.value + diff.averagevalue * ((itemid < inputitemid) ? 1 : -1));
                        itemrating.freq += diff.freq;
                    }
                }
                predictions.add(itemid, itemrating.averagevalue);               
            }
            return predictions;
        }
        public static void test()
        {
            slopeone test = new slopeone();
            dictionary<int, float> userrating = new dictionary<int, float>();
            userrating.add(1, 5);
            userrating.add(2, 4);
            userrating.add(3, 4);
            test.adduserratings(userrating);
            userrating = new dictionary<int, float>();
            userrating.add(1, 4);
            userrating.add(2, 5);
            userrating.add(3, 3);
            userrating.add(4, 5);
            test.adduserratings(userrating);
            userrating = new dictionary<int, float>();
            userrating.add(1, 4);
            userrating.add(2, 4);
            userrating.add(4, 5);
            test.adduserratings(userrating);
            userrating = new dictionary<int, float>();
            userrating.add(1, 5);
            userrating.add(3, 4);
            idictionary<int, float> predictions = test.predict(userrating);
            foreach (var rating in predictions)
            {
                console.writeline("item " + rating.key + " rating: " + rating.value);
            }
        }
    }
}