Natural Language Processing

This module contains methods to accomplish several tasks related to the field of natural language processing (NLP) such as:

P R E P R O C E S S I N G:

Although there are many high-level API available, performing the text cleaning manually can give some advantages in regards of customization.

Loading the data and selecting relevant parts
Removing punctuation
Removing words shorter than a choosen length
Replace numbers with their word-based equivalent
Removing stopwords
Lemmatization
Tokenization

N L P:

Sentiment Analysis
Part-of-Speech-Tagging (POS-Tagging)
Named-Entity-Recognition (NER)
TF-IDF Scoring
Cosine Similarity
MinHashing
WordEmbedding
Latent Semantic Analysis (LSA)