anchor.diff:  (defmethod generate-document-similarity-vectors ((collection document-collection))
     (with-accessors ((documents documents)) collection
       (loop for document-a in documents
  -          do (setf (similarity-vector document-a)
  -                   (loop for document-b in documents
  -                         collect (cons (cosine-similarity document-a document-b) document-b))))))
  +          do (loop for document-b in documents
  +                   do (setf (gethash document-b (edges document-a))
  +                            (cosine-similarity document-a document-b))))))
   
   (defmethod text-rank ((collection document-collection) &key (epsilon 0.001)
                                                               (damping 0.85)
  
positive.code:   (let ((collection (make-instance 'document-collection)))
      (loop for sentence in (sentence-tokenize text)
            do (add-document collection
                             (make-instance 'document-similarity-vector
                                            :string-contents sentence)))
      (word-count-vectorize-documents collection)
      (generate-document-similarity-vectors collection)
  
negative.code: 
  ;;; text-rank.lisp -- implementation of textrank algorithm
  
  (defclass document-vertex (document)
    ((edges :accessor edges :initform (make-hash-table)
            :documentation "The keys of the hash table represent the
            edges, the values of the hash table represent the edge
            weights.")))
  
  (defmethod word-count-vectorize ((document document) dictionary)
    "Transform a document into a vector using word counts."
  