Word2Vec was a fork or based on a more exhuastive vector space approach here https://www.kaggle.com/c/word2vec-nlp-tutorial/forums/t/12349/word2vec-is-based-on-

Word2Vec was a fork or based on a more exhuastive vector space approach here https://www.kaggle.com/c/word2vec-nlp-tutorial/forums/t/12349/word2vec-is-based-on-an-approach-from-lawrence-berkeley-national-lab https://www.kaggle.com/c/word2vec-nlp-tutorial/forums/t/1234... I've compared the summarization to others like OTS http://libots.sourceforge.net/ http://libots.sourceforge.net/ which I believe strictly relies on TF-IDF and it seems better and allows for context to control the summarization. Other similar approaches might be based on Latent Semantic Analysis, Latent Semantic Indexing or LDA.