Category Archives: Natural Language Processing

Slideshare (6): Cross-lingual Paper reading notes

During this summer, I did a project on cross-lingual NLP tasks. Recently I was working my notes and I organized them into a better format. I would like to share some of the notes with the readers who might be interested in this topic. Cross_lingual_NLP(PDF) Papers covered: A Robust Abstractive System for Cross-Lingual Summarization MASS:Continue reading “Slideshare (6): Cross-lingual Paper reading notes”

Deep Learning 17: text classification with BERT using PyTorch

Why BERT If you are a big fun of PyTorch and NLP, you must try to use the PyTorch based BERT implementation! If you have your own dataset and want to try the state-of-the-art model, BERT is a good choice. Please check the code from https://github.com/huggingface/pytorch-pretrained-BERT to get a close look. However, in this post,Continue reading “Deep Learning 17: text classification with BERT using PyTorch”

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

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 aContinue reading “NLP 05: From Word2vec to Doc2vec: a simple example with Gensim”