1. Natural Language Processing Ellen Back, LIS489, Spring 2015

2. Natural Language Processing (NLP) is the branch of computer science dedicated to creating systems that allow computers to communicate with people using everyday language.

3. Natural language is very ambiguous and must be disambiguated.

4. For example…. Ban on Nude Dancing on Governor's Desk Iraqi Head Seeks Arms Juvenile Court to Try Shooting Defendant TeacherStrikesIdleKids StolenPaintingFoundbyTree Local High School Dropouts Cut in Half Red Tape Holds Up New Bridges Clinton Wins on Budget, but More Lies Ahead Hospitals Are Sued by 7 Foot Doctors Kids Make Nutritious Snacks

5. NLP goals can be far-reaching, that computers can reason about and understand any piece of text, or more down-to-earth such as context sensitive spelling correction. Context spelling correction example: Chocolate chip cookies are my favorite desert.

6. Using NLP, IBM Watson Beats Human Champions at Jeopardy! https://www.youtube.com/watch?v=_Xcmh1LQB9I https://www.youtube.com/watch?v=DywO4zksfXw http://www.ibm.com/smarterplanet/us/en/ibmwatson/what-is-watson.html

7. Historically, both logical and probabilistic methods have found wide application in NLP. A natural language parser is a program that determines the grammatical structure of sentences, for instance, which groups of words go together (as "phrases") and which words are the subject or object of a verb. Probabilistic parsers use knowledge of language gleamed from hand-parsed sentences to try to produce the most likely analysis of new sentences. These statistical parsers still make some errors, but commonly work rather well. Their development was one of the most significant breakthroughs in natural language processing in the 1990s. Juvenile Court to Try Shooting Defendant You can try out the Stanford parser online.try out the Stanford parser online.

8. The Stanford NLP Group works on algorithms that allow computers to process and understand human languages. Their work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, machine translation, probabilistic parsing and tagging, biomedical information extraction, grammar induction, word sense disambiguation, automatic question answering, and text to 3D scene generation. Birthplace of Siri: voice recognition + sentence parsing https://www.youtube.com/watch?v=nfoudtpBV68

9. . At Microsoft the NLP Research team uses a mix of knowledge-engineered and statistical/machine-learning techniques to disambiguate and respond to natural language input. Their work is significant for applications like text critiquing, information retrieval, question answering, summarization, gaming, and translation. The grammar checkers in Office for English, French, German, and Spanish are products of their research; Encarta employs their technology to retrieve answers to user questions; Intellishrink uses natural language technology to compress cellphone messages; Microsoft Product Support uses machine translation software to translate the Microsoft Knowledge Base into other languages.

10. Programmers, computers and users all benefit from Natural Language Processing. To this end, companies and universities are constantly trying to improve the human-computer interaction.

11. For more information about Microsoft and Stanford Research: http://research.microsoft.com/en-us/groups/nlp/ http://nlp.stanford.edu/

12. For general information about NLP: http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd- 8412-263f1a472f5a (Wonderful course from Stanford with links to video lectures and transcripts) http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd- 8412-263f1a472f5a http://www.cs.utexas.edu/~mooney/cs388/ http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6- 864-advanced-natural-language-processing-fall-2005/ (Because you know you want the advanced level from MIT! ) http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6- 864-advanced-natural-language-processing-fall-2005/

13. Journals such as Computational Linguistics and Computer Speech & Language will provide up-to-date information in the field.

14. Sources Artificial Intelligence, Natural Language Processing. (n.d.) Engineering. Stanford University. Retrieved from http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd-8412- 263f1a472f5a http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd-8412- 263f1a472f5a Intro to NLP. (n.d.). The University of Washington. Retrieved from http://courses.cs.washington.edu/courses/csep573/12au/lectures/19-nlp.pdf Natural Language Processing. (2015). Research. Microsoft. Retrieved from http://research.microsoft.com/en-us/groups/nlp/ http://research.microsoft.com/en-us/groups/nlp/ Natural Language Processing. (n.d.). The University of Texas. Retrieved from http://www.cs.utexas.edu/~mooney/cs388/ The Stanford NLP Group. (n.d.). Stanford University Natural Language Processing. Retrieved from http://nlp.stanford.edu/http://nlp.stanford.edu/