4 ms·
I've been using LASER from Facebook Research via https://github.com/yannvgn/laserembeddings https://github.com/yannvgn/laserembeddings to accept multi-lingual i
by chartpath 6y ago
I've been using LASER from Facebook Research via https://github.com/yannvgn/laserembeddings https://github.com/yannvgn/laserembeddings to accept multi-lingual input in front of the the domain-specific models for recommendations and stuff (that are trained on English annotated examples).
- zburatorul 6y agoThis sounds interesting. Can you share more please? It sounds like there is some multilingual input text on the basis of which you make recommendations, but I think you would have called that a search engine rather than recommender.
- chartpath 6y agoThat's true, I'm making recommendations based on Multinomial Naive Bayes (and SGDClassifier) over custom TF-IDF bags of words, so it is like search plus text classification. And some endpoints do just check the cosine or Jaccard distance between things. There is a lot of overlap between search and NLP. My approach to AI is somewhat conservative because of working in a law-adjacent field where explainability is paramount. When it comes to getting "smart" I prefer forward-chaining logic over facts, and facts include predictions from models too. But at least there is a "judge"/engine to coordinate how the predictions from the ensemble of models maps to actions. I love me some pertained neural nets, but use them more as black box appliances.
- krasi0 6y agoWhich forward-chaining engine do you use? Something based on prolog?
- chartpath 6y agoCurrently https://github.com/nilp0inter/experta https://github.com/nilp0inter/experta but https://github.com/noxdafox/clipspy https://github.com/noxdafox/clipspy seems nice, I just shied away from using it due to uneasiness about FFI and debugging, even though the original CLIPS is still awesome and has a very interesting manual. There's also https://github.com/jruizgit/rules https://github.com/jruizgit/rules but haven't tried it yet.