| 词条 | Draft:Rasa NLU |
| 释义 |
| title = Rasa NLU | name = Rasa NLU | logo = File:Rasa nlu horizontal purple.svg | developer = [https://rasa.com Rasa Technologies], [https://github.com/RasaHQ/rasa_nlu/graphs/contributors various] | released = December 2016.[1] | repo = {{URL|https://github.com/RasaHQ/rasa_nlu}} | programming language = Python | genre = Natural language processing | license = Apache License | website = [https://forum.rasa.com/ Rasa Forum] }}Rasa NLU is an open-source library for Natural Language Processing[2][3]. The library is published under the Apache 2.0 license and enables intent classification and entity extraction of natural language using word embeddings for the use in AI assistants and chatbots.[4] Unlike most NLU solutions it is hosted completely on-premise making it a viable option for companies handling sensitive data or developing in house expertise.[5] Rasa NLU integrates with common backend-systems providing pre-trained word vectors like SpaCy or fastText. It is also possible to use tensorflow components to train new custom word vectors on a specific dataset. Recently it was announced as one of the top 10 open source machine learning projects on Github.[6] Main Features
See also
References1. ^{{cite web |last1=Mannes |first1=John |title=Rasa NLU gives developers an open source solution for natural langauge processing |url=https://techcrunch.com/2016/12/16/nlpforeveryone/ |publisher=Techcrunch}} 2. ^{{cite web |title=Open-source intent recognition in NLP & NLU|url=https://nology.de/open-source-intent-recognition-classification-nlp-nlu |website=Nology |accessdate=31 August 2018}} 3. ^{{cite web |last1=Rodriguez |first1=Jesus |title=Technology Fridays: An overview of Rasa, the best NLP Platform you never heard of |url=https://medium.com/@jrodthoughts/technology-fridays-an-overview-of-rasa-the-best-nlp-platform-you-never-heard-of-633b25f43845 |accessdate=31 August 2018}} 4. ^{{cite web |title=Rasa NLU |url=https://rasa.com/products/rasa-nlu/ |website=Rasa |accessdate=31 August 2018}} 5. ^{{cite web |last1=Olson |first1=Parmy |title=Google, Microsoft And Startups Are Going To War On Chatbot Technology |url=https://www.forbes.com/sites/parmyolson/2018/07/27/google-microsoft-and-startups-are-going-to-war-on-chatbot-technology/#33af81be61b6 |website=Forbes |publisher=Forbes |accessdate=18 February 2019}} 6. ^{{cite web |last1=WIGGERS |first1=KYLE |title=Top ML Projects on Github |url=https://venturebeat.com/2019/01/24/github-numpy-and-scipy-are-the-most-popular-packages-for-machine-learning-projects/ |website=VentureBeat |accessdate=18 February 2019}} 7. ^{{cite web |title=Understanding the NLU pipleine |url=https://rasa.com/docs/nlu/master/choosing_pipeline/#understanding-the-rasa-nlu-pipeline |website=Rasa |accessdate=31 August 2018}} 8. ^{{cite web |last1=Petraityte |first1=Justina |title=How to handle multiple intents per input using Rasa NLU TensorFlow pipeline |url=https://blog.rasa.com/how-to-handle-multiple-intents-per-input-using-rasa-nlu-tensorflow-pipeline/ |website=Rasa |accessdate=31 August 2018}} 9. ^{{cite web |title=Entity Extraction |url=https://rasa.com/docs/nlu/master/entities/ |website=Rasa |accessdate=31 August 2018}} 10. ^{{cite web |last1=Nichol |first1=Alan |title=Supervised Word Vectors from Scratch |url=https://medium.com/rasa-blog/supervised-word-vectors-from-scratch-in-rasa-nlu-6daf794efcd8 |website=Medium.com |publisher=Rasa |accessdate=18 February 2019}} External links
deleted unrelated information about company and other products, added independent sources, redefined main features, made a stub for now{{AFC submission|||ts=20190218181554|u=DominikRo|ns=118}} |
| 随便看 |
|
开放百科全书收录14589846条英语、德语、日语等多语种百科知识，基本涵盖了大多数领域的百科知识，是一部内容自由、开放的电子版国际百科全书。