public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
var artistIndices = first.ArtistIndices.Union(second.ArtistIndices).ToList();
foreach (var artistIndex in artistIndices)
{
var rX = 1.0f;
if (first.RatingsByArtistIndexLookupTable.ContainsKey(artistIndex))
{
rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value;
}
var rY = 1.0f;
if (second.RatingsByArtistIndexLookupTable.ContainsKey(artistIndex))
{
rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value;
}
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
return(sumNum / (float)(Math.Sqrt(sumX) * Math.Sqrt(sumY)));
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
var artistIndices = first.ArtistIndices.Union(second.ArtistIndices).ToList();
foreach (var artistIndex in artistIndices)
{
var rX = 1.0f;
if (first.RatingsByArtistIndexLookupTable.ContainsKey(artistIndex))
rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value;
var rY = 1.0f;
if (second.RatingsByArtistIndexLookupTable.ContainsKey(artistIndex))
rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
return sumNum / (float)(Math.Sqrt(sumX) * Math.Sqrt(sumY));
}
public List <SimilarUser <ISimpleKnnUser> > CalculateKNearestNeighbours(ISimpleKnnUser user, IEnumerable <ISimpleKnnUser> users, int nearestNeighboursCount)
{
var neighbours = new List <SimilarUser <ISimpleKnnUser> >();
foreach (var neighbour in users)
{
if (neighbour == user)
{
continue;
}
var s = CalculateSimilarity(user, neighbour);
if (s <= 0.0)
{
continue;
}
neighbours.Add(new SimilarUser <ISimpleKnnUser>(neighbour, s));
neighbours.Sort();
while (neighbours.Count > nearestNeighboursCount)
{
neighbours.RemoveAt(neighbours.Count - 1);
}
}
return(neighbours);
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
var artistIndices = first.ArtistIndices.IntersectSorted(second.ArtistIndices).ToList();
if (artistIndices.Count <= 0)
{
return(0.0f);
}
foreach (var artistIndex in artistIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var mass = artistIndices.Count * 2.0f / (first.Ratings.Count + second.Ratings.Count);
return(sumNum / (float)(Math.Sqrt(sumX) * Math.Sqrt(sumY)) * (mass));
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
var artistIndices = first.ArtistIndices.IntersectSorted(second.ArtistIndices).ToList();
var rXavg = first.Ratings.Average(r => r.Value);
var rYavg = second.Ratings.Average(r => r.Value);
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
foreach (var artistIndex in artistIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var firstIndices = first.ArtistIndices.Except(artistIndices).ToList();
foreach (var artistIndex in firstIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = 1.0f - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var secondIndices = second.ArtistIndices.Except(artistIndices).ToList();
foreach (var artistIndex in secondIndices)
{
var rX = 1.0f - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
return(Math.Abs(sumNum / (float)(Math.Sqrt(sumX) * Math.Sqrt(sumY))));
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
var artistIndices = first.ArtistIndices.IntersectSorted(second.ArtistIndices).ToList();
var rXavg = first.Ratings.Average(r => r.Value);
var rYavg = second.Ratings.Average(r => r.Value);
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
foreach (var artistIndex in artistIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var firstIndices = first.ArtistIndices.Except(artistIndices).ToList();
foreach (var artistIndex in firstIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = 1.0f - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var secondIndices = second.ArtistIndices.Except(artistIndices).ToList();
foreach (var artistIndex in secondIndices)
{
var rX = 1.0f - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
return Math.Abs(sumNum / (float)(Math.Sqrt(sumX) * Math.Sqrt(sumY)));
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
var artistIndices = first.ArtistIndices.IntersectSorted(second.ArtistIndices).ToList();
if (artistIndices.Count <= 0)
{
return(0.0f);
}
var rXavg = 0.0f;
var rYavg = 0.0f;
foreach (var artistIndex in artistIndices)
{
rXavg += first.RatingsByArtistIndexLookupTable[artistIndex].Value;
rYavg += second.RatingsByArtistIndexLookupTable[artistIndex].Value;
}
rXavg /= artistIndices.Count;
rYavg /= artistIndices.Count;
foreach (var artistIndex in artistIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var mass = artistIndices.Count * 2.0f / (first.Ratings.Count + second.Ratings.Count);
var r = sumNum / (float)(Math.Sqrt(sumX * sumY)) * (mass);
if (float.IsNaN(r))
{
return(0.0f);
}
return(Math.Abs(r));
}
public List<SimilarUser<ISimpleKnnUser>> CalculateKNearestNeighbours(ISimpleKnnUser user, IEnumerable<ISimpleKnnUser> users, int nearestNeighboursCount)
{
var neighbours = new List<SimilarUser<ISimpleKnnUser>>();
foreach (var neighbour in users)
{
if (neighbour == user)
continue;
var s = CalculateSimilarity(user, neighbour);
if (s <= 0.0)
continue;
neighbours.Add(new SimilarUser<ISimpleKnnUser>(neighbour, s));
neighbours.Sort();
while (neighbours.Count > nearestNeighboursCount)
neighbours.RemoveAt(neighbours.Count - 1);
}
return neighbours;
}
public float GetSimilarity(ISimpleKnnUser first, ISimpleKnnUser second)
{
float sumNum = 0.0f,
sumX = 0.0f,
sumY = 0.0f;
var artistIndices = first.ArtistIndices.IntersectSorted(second.ArtistIndices).ToList();
if (artistIndices.Count <= 0)
return 0.0f;
var rXavg = 0.0f;
var rYavg = 0.0f;
foreach (var artistIndex in artistIndices)
{
rXavg += first.RatingsByArtistIndexLookupTable[artistIndex].Value;
rYavg += second.RatingsByArtistIndexLookupTable[artistIndex].Value;
}
rXavg /= artistIndices.Count;
rYavg /= artistIndices.Count;
foreach (var artistIndex in artistIndices)
{
var rX = first.RatingsByArtistIndexLookupTable[artistIndex].Value - rXavg;
var rY = second.RatingsByArtistIndexLookupTable[artistIndex].Value - rYavg;
sumNum += rX * rY;
sumX += rX * rX;
sumY += rY * rY;
}
var mass = artistIndices.Count * 2.0f / (first.Ratings.Count + second.Ratings.Count);
var r = sumNum / (float)(Math.Sqrt(sumX * sumY)) * (mass);
if (float.IsNaN(r))
return 0.0f;
return Math.Abs(r);
}
public override float CalculateSimilarity(ISimpleKnnUser user, ISimpleKnnUser neighbour)
{
return(base.CalculateSimilarity(user, neighbour) * ContentSimilarityEstimator.GetSimilarity(user, neighbour));
}
public override float CalculateSimilarity(ISimpleKnnUser user, ISimpleKnnUser neighbour)
{
return base.CalculateSimilarity(user, neighbour) * ContentSimilarityEstimator.GetSimilarity(user, neighbour);
}
public virtual float CalculateSimilarity(ISimpleKnnUser user, ISimpleKnnUser neighbour)
{
var s = SimilarityEstimator.GetSimilarity(user, neighbour);
return s;
}
public virtual float CalculateSimilarity(ISimpleKnnUser user, ISimpleKnnUser neighbour)
{
var s = SimilarityEstimator.GetSimilarity(user, neighbour);
return(s);
}
