Natural Language Processing Crash Course
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Charlie Greenbacker, founder and co-organizer of the DC NLP meetup group, provides a "crash course" in Natural Language Processing techniques and applications.
Natural Language Processing Crash Course
- 1. NLP ＾Crash Course￣ Charlie Greenbacker dcnlp.org
- 2. Agenda ? Introduction & Motivation ? Famous Examples ? Basics ? Major Task Areas ? Protips ? Resources
- 3. Introduction & Motivation By ＾NLP￣ we mean... Natural Language Processing (#NLProc) aka Computational Linguistics,Text Analytics, etc. not Neuro-linguistic Programming! (#NLP)
- 4. Introduction & Motivation Natural Language Processing is... Using computers to process (i.e., analyze, understand, generate, etc.) natural human languages (e.g., English, Chinese, Klingon). Hello, world! 低挫弊順
- 5. That sounds hard... why should I care? ? Most of the knowledge created by humans is unstructured text (information overload) ? Need some way to make sense of it all ? Enable quantitative analysis of text data Introduction & Motivation
- 6. Famous Examples Siri (Apple, SRI, Nuance) Speech Recognition/Generation IBM Watson Question Answering Google Translate MachineTranslation
- 7. Basics ? Segmentation ? Part-of-speech tagging ? Noun phrase (NP) chunking ? Parsing ? Word sense disambiguation
- 8. Basics ? Stop words, stemming/lemmatization ? Frequency analysis (terms, ngrams,TF-IDF) ? Machine learning (classi?cation, clustering, recommendation)
- 9. Major Task Areas Question Answering ? Match query with knowledge base ? Closed domain vs open domain ? Reasoning about intent of question
- 10. Major Task Areas Speech Recognition ? Speech to text ? Trained/untrained user models ? Voice-based interfaces
- 11. Major Task Areas Named Entity Recognition ? Entity extraction ? Persons, organizations, location ? Grammar, syntax, phrasing
- 12. Major Task Areas Entity Resolution ? Linking names to ground truth ? Disambiguating similar names
- 13. Major Task Areas Co-reference Resolution ? Finding antecedents for pronouns ? Name resolution
- 14. Major Task Areas Relationship Extraction ? Attribute values ? SVO triples ? Populating ontologies
- 15. Major Task Areas Information Retrieval ? Query expansion ? Relevancy of results ? ＾More like this￣
- 16. Major Task Areas Assistive Technologies ? Text simpli?cation ? Predictive text input ? Alternative interfaces
- 17. Major Task Areas NLG + Automatic Summarization ? Generating text from data ? Extractive summarization ? Abstractive summarization
- 18. Major Task Areas Machine Translation ? From source to target, and back! ? Single terms work... sometimes ? Idioms, metaphors, cultural references
- 19. Major Task Areas Sentiment Analysis ? Polarity, intensity, direction ? "Easy" for movie/product reviews ? "Impossible" for nearly anything else
- 20. Protips ? Domain adaptation (retrain your models, social media != news) ? Assume everything is in beta (error rates compound, translate last, consult the research literature) ? Evaluation is essential (human judges,＾gold standard￣ data, cross-validation, appropriate metrics)
- 21. Resources (toolkits) Stanford CoreNLP Java, GPL Apache OpenNLP Java,Apache License NLTK Python,Apache License
- 22. Resources (books) Natural Language Processing with Python Bird, Klein, and Loper Speech and Language______________ Processing______________ Jurafsky and Martin______________ Foundations of Statistical Natural Language Processing Manning and Sch┨tze
- 23. Resources (groups) ACL (Association for Computational Linguistics) Conferences,Workshops, Journals, SIGs DC NLP NLP Meetups Data Community DC NLPWorkshops