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📢 Seriously, We can't go with Big5 or other non structured descriptions to diverse large amount of characters 👨👩👦👦 from many books 📚. Instead, The factorization + open-psychometrics antonyms extracted from dialogues is a key 🔑 for automatic character profiling that purely relies on book content 📖. With that, happy to share delighted to share with you 🙌 more on this topic in YouTube video:
https://youtu.be/UQQsXfZyjjc
🔑 From which you will find out:
✅ How to perform book processing 📖 aimed at personalities extraction
✅ How to impute personalities 👨👩👦👦 and character network for deep learning 🤖
✅ How to evaluate 📊 advances / experiment findings 🧪
Additional materials:
🌟 Github: https://github.com/nicolay-r/book-persona-retriever
📜 Paper: https://www.dropbox.com/scl/fi/0c2axh97hadolwphgu7it/rusnachenko2024personality.pdf?rlkey=g2yyzv01th2rjt4o1oky0q8zc&st=omssztha&dl=1
📙 Google-colab experiments: https://colab.research.google.com/github/nicolay-r/deep-book-processing/blob/master/parlai_gutenberg_experiments.ipynb
🦜 Task: https://github.com/nicolay-r/parlai_bookchar_task/tree/master
https://youtu.be/UQQsXfZyjjc
🔑 From which you will find out:
✅ How to perform book processing 📖 aimed at personalities extraction
✅ How to impute personalities 👨👩👦👦 and character network for deep learning 🤖
✅ How to evaluate 📊 advances / experiment findings 🧪
Additional materials:
🌟 Github: https://github.com/nicolay-r/book-persona-retriever
📜 Paper: https://www.dropbox.com/scl/fi/0c2axh97hadolwphgu7it/rusnachenko2024personality.pdf?rlkey=g2yyzv01th2rjt4o1oky0q8zc&st=omssztha&dl=1
📙 Google-colab experiments: https://colab.research.google.com/github/nicolay-r/deep-book-processing/blob/master/parlai_gutenberg_experiments.ipynb
🦜 Task: https://github.com/nicolay-r/parlai_bookchar_task/tree/master