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Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media
Preeti Bhargava
|
Nemanja Spasojevic
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Guoning Hu
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Paper Details:
Month: September
Year: 2017
Location: Copenhagen, Denmark
Venue:
WNUT |
WS |
Citations
URL
No Citations Yet
https://en.wikipedia.org/wiki/Information_
https://youtu.be/U-o6Efh6TZc
https://klout.com
https://klout.com/corp/score
http://support.gnip.com/enrichments/klout
https://www.lithium.com/products/
https://www.lithium.com/products/
https://goo.gl/vtZDqE#Klout_Perks
https://goo.gl/CLcx9p#Cinch
https://github.com/klout/opendata/tree/
https://github.com/klout/opendata/tree/
https://developers.google.com/
https://github.com/shuyo/
https://docs.oracle.com/javase/7/docs/api/
http://lucene.apache.org/core/4_5_0/
https://lucene.apache.org/core/4_5_0/
https://github.com/klout/opendata/blob/
https://cloud.google.com/natural-language/
http://www.opencalais.com/opencalais-demo/
https://alchemy-language-demo.mybluemix
http://corenlp.run/
https://www.ambiverse.com/
https://github.com/aritter/twitter_nlp
Field Of Study
Task
Information Extraction
Sentiment Analysis
Language
Chinese
English
Spanish
Dataset
Social Media
Twitter
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