Natural Language Processing
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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.
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Natural Language Processing
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- 5. The Processing Pipeline Raw > Tokenized > Normalized > Vocabulary
Hinweis der Redaktion
- 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.
- For science & engineering NLP could be used for data modeling, data mining, and knowledge discovery (example)
- Tech Demo 1: Process raw text from the web.
- Let’s explore a context where NLP can support HCI research.