Natural Language Processing with Ruby

on YouTube ↗39m

" summary

Begins from a concrete claim: Ruby can leverage mature NLP stacks by running on JRuby + JDK 7 to call Java libraries. The demo uses OpenNLP and Snowball to tokenize text remove stop words stem words rank top tokens detect sentences and extract a 3-sentence summary by scoring sentences The code loads trained English models from OpenNLP counts stems to rank words and returns the top three sentences showing the approach is simple fast and practically useful.

AI-written summary · about

" chapters (22)

1. 0:00Start
2. 1:24Past Employers
3. 2:48Goals and Agenda
4. 3:10Introduction to Natural Language Processing
5. 3:50Natural Language Processing
6. 4:39Common Solutions
7. 13:58Facts about Data Growth
8. 17:13Machine Learning
9. 18:26Basic Building Blocks behind Natural Language Processing
10. 19:21Named Entity Recognition
11. 21:56Linguistics
12. 22:33Punk Segmenter
13. 23:28Ruby Stemmer
14. 25:29Jruby
15. 27:07Java
16. 27:59Summarizing Text
17. 29:40Ruby Wordnet
18. 29:58Identify Synonyms and Related Words Wordnet
19. 30:29Tokenize the Text
20. 32:49Extract the Sentences
21. 33:09Rank the Sentences
22. 33:36Create the Summary

" related talks

• 27mNatural Language Processing with RubyKonstantin Tennhard Natural Language Processing · ArrrrCamp 2014
• 33mSyntax Isn't Everything: NLP for RubyistsAja Hammerly · RailsConf 2017
• 31mNatural Language Processing & JavaDeepu Xavier · Eclipse Summit India 2017
• 29mJRuby on ElephantsTim Cowlishaw · Ru3y Manor 3
• 31mSyntax Isn't Everything: NLP For RubyistsJanice Shiu · RubyConf MY 2017
• 35mIntelligent Ruby: Getting Started with Machine LearningIlya Grigorik · GoGaRuCo 2010
• 30mRuby-us Hagrid: Writing Harry Potter with RubyAlex Peattie · RubyConf 2018
• 46mPractical Machine Learning and RailsRyan Stout, Andrew Cantino · RailsConf 2012