Posted in Natural Language Processing, Problem Shooting, Python, Theory

Working with ROUGE 1.5.5 Evaluation Metric in Python

If you use ROUGE Evaluation metric for text summarization systems or machine translation systems, you must have noticed that there are many versions of them. So how to get it work with your own systems with Python? What packages are helpful? In this post, I will give some ideas based on engineering’s view (which means I am not going to introduce what is ROUGE). I also suffered from few issues and finally got them solved. My methods might not be the best ways but they worked.

Continue reading “Working with ROUGE 1.5.5 Evaluation Metric in Python”

Posted in Algorithm, Natural Language Processing, Python, Theory

NLP 05: From Word2vec to Doc2vec: a simple example with Gensim

 

Introduction

First introduced by Mikolov 1 in 2013, the word2vec is to learn distributed representations (word embeddings) when applying neural network. It is based on the distributed hypothesis that words occur in similar contexts (neighboring words) tend to have similar meanings. Two models here: cbow ( continuous bag of words) where we use a bag of words to predict a target word and skip-gram where we use one word to predict its neighbors. For more, although not highly recommended, have a look at TensorFlow tutorial here. Continue reading “NLP 05: From Word2vec to Doc2vec: a simple example with Gensim”