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Natural Language Processing (NLP) Barely Skimming The Surface Mike Long — TW SF Home Office Day
Agenda ,[object Object],[object Object],[object Object],[object Object]
Exploring language models flickr.com/harvardmuseumofnaturalhistory
Knowledge discovery flickr.com/mcgervey
The Processing Pipeline Raw > Tokenized > Normalized > Vocabulary
Listen for, and make note of: ,[object Object],[object Object],[object Object],[object Object],[object Object]
 

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Natural Language Processing

Editor's Notes

  1. NLP is important for scientific, economic, and cultural reasons. It is experiencing rapid growth as its theories and methods are deployed in a variety of new language technologies. It is important for a wide range of people to have a working knowledge of NLP. Within industry, this includes people in HCI, business information analysis, and website development. NLP could be as simple as counting the number of times a letter occurs in a paragraph of text or as complex as understanding human conversations, at least to the level of giving useful responses to people. From a Arts & Humanities perspective, NLP could be used to explore language models (information retrieval, part-of-speech tagging, speech recognition) and test empirical claims.
  2. For science & engineering NLP could be used for data modeling, data mining, and knowledge discovery (example)
  3. Tech Demo 1: Process raw text from the web.
  4. Let’s explore a context where NLP can support HCI research.