Get the text similarity you need with word embeddings

A 5 minute talk at PyData London on 7 Feb.

Transcript

1. Get the word similarity you need Lev Konstantinovskiy Community Manager at Gensim @teagermylk http://rare-technologies.com/
2. Streaming We turn NLP papers into industrial Python code.
3. Credits Parul Sethi Undergraduate student University of Delhi, India RaReTech Incubator program Added WordRank to Gensim http://rare-technologies.com/incubator/
4. Business Problems
5. Business Problems “What does Elizabeth think about Mr Darcy?” “Male characters in Pride and Prejudice?”
6. Two Different Business Problems 1) What words are in the topic of “Darcy”? 2) What are the Named Entities in the text?
7. P&P is only 120k words
8. Closest word to “king”? Trained on Wikipedia 17m words Attribute Interchangeable Both
9. Tensorflow has awesome viz!
10. How to get the similarity you need My similar words must be Associated Interchangeable I want to describes the word’s Topic Function I want to Know what doc is about Recognize names Then I should run Wordrank (even on small corpus, 1m words) or Word2vec skipgram big window needs large corpus >5m words Word2vec skipgram small window or FastText or VarEmbed
11. Rare and Frequent words are incomprehensible
12. Thanks! Lev Konstantinovskiy github.com/tmylk @teagermylk Gensim T-shirt question: How many words are in Pride and Prejudice?