Update README.md

ddangelov · Mar 23, 2020 · e8af012 · e8af012
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@@ -33,6 +33,7 @@ attracted the documents to the dense area are the topic words.
 **The Algorithm:**
 
 1. Create jointly embedded document and word vectors using [Doc2Vec](https://radimrehurek.com/gensim/models/doc2vec.html).
+>Documents will be placed to other similar documents and close to most distinguishing words. 
 ![Joint Document and Word Embedding](images/doc_word_embedding.svg)
 2. Create lower dimensional embedding of document vectors using [UMAP](https://github.com/lmcinnes/umap)
 3. Find dense areas of documents using [HDBSCAN](https://github.com/scikit-learn-contrib/hdbscan)