Recommender System

This is a detailed reproduction of ref. Sunny Summary # 3 steps: preprocessing.py preprocessing to extract: author, average sentence length, average word length, punctuation profile, sentiment scores, part-of-speech profiles/tags (only in code, not taken into the csv). TFIDF.py content-wise k-means clustering (on TFIDF scores) to get: 3 levels/degrees of clustering/classification results. knn.py knn search on the results of step 1 and 2 to get: recommendations (k=15 by default). Preprocessing # pip2 install nltk pip2 install twython # optional ? ...