Linked Data and Data Science
Understanding Gender Roles in Movies with Text Mining
I have a new visual essay up at The Pudding, using text mining to explore how women are portrayed in film.   In April 2016, we broke down film dialogue by gender. The essay presented an imbalance in which men delivered more lines than women across 2,000 screenplays. But... Read more
Natural Language Processing in a Kaggle Competition for Movie Reviews
I decided to try playing around with a Kaggle competition. In this case, I entered the “When bag of words meets bags of popcorn” contest. This contest isn’t for money; it is just a way to learn about various machine learning approaches. The competition was trying to showcase... Read more
Word2Vec – the world of word vectors
Have you ever wondered how a chatbot can learn about the meaning of words in a text? Does this sound interesting? Well, in this blog we will describe a very powerful method, Word2Vec, that maps words to numbers (vectors) in order to easily capture and distinguish their meaning. We will briefly describe how Word2Vec... Read more
Word embeddings in 2017: Trends and future directions
Table of contents: Subword-level embeddings OOV handling Evaluation Multi-sense embeddings Beyond words as points Phrases and multi-word expressions Bias Temporal dimension Lack of theoretical understanding Task and domain-specific embeddings Embeddings for multiple languages Embeddings based on other contexts The word2vec method based on skip-gram with negative... Read more
See first-hand how you can bring an NLP application to life. Last week I introduced No Jitter readers to Natural Language Processing (NLP) and Facebook’s free NLP service, wit.ai. I wrote about intents and entities, and how they work together to convert human language into actionable... Read more
This post is the first of a two-part series in which we apply NLP techniques to analyze articles about big data, data science, and AI. If you are tired of the hassles of web scraping, then this post might be just for you. I occasionally web scrape news... Read more
Multi-Task Learning Objectives for Natural Language Processing
In a previous blog post, I discussed how multi-task learning (MTL) can be used to improve the performance of a model by leveraging a related task. Multi-task learning consists of two main components: a) The architecture used for learning and b) the auxiliary task(s) that are trained... Read more
Enhancing Customer Experience with Natural Language Processing
Processing language into actionable components is the future of communication. If you talk to a man in a language he understands, that goes to his head. If you talk to him in his language, that goes to his heart. — Nelson Mandela I would venture to... Read more
Word Vectors and SAT Analogies
This reminded me of SAT analogy questions, which disappeared from the SAT in 2005, but looked like this: PALTRY : SIGNIFICANCE :: A. redundant : discussion B. austere : landscape C. opulent : wealth D. oblique : familiarity E. banal : originality The king/queen example is not difficult, and... Read more