docs: def bm25_weight(X, K1=100, B=0.8):
      """ Weighs each row of a sparse matrix X  by BM25 weighting """
      # calculate idf per term (user)
      X = coo_matrix(X)
  
      N = float(X.shape[0])
      idf = log(N) - log1p(bincount(X.col))
  
      # calculate length_norm per document (artist)
      row_sums = numpy.ravel(X.sum(axis=1))
      average_length = row_sums.mean()
      length_norm = (1.0 - B) + B * row_sums / average_length
  
      # weight matrix rows by bm25
      X.data = X.data * (K1 + 1.0) / (K1 * length_norm[X.row] + X.data) * idf[X.col]
      return X