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Improving Accuracy of Named Entity Recognition on Social Media Data

Description: We present a system for improving the accuracy of one NLP technique, Named Entity Recognition or NER, on Twitter data by training a recognizer specifically for this type of data. This training data is obtained from the Amazon Mechanical Turk crowdsourcing platform.

Type: Poster

Authors: Will Murnane, Tim Finin, and Nicholas Keller

Date: May 08, 2010

Version: 2

Tags: poster, 2010, csee research review, mturk, amt, ner, natural language processing, twitter

Format: PDF Document (Need a reader? Get one here)

Number of downloads: 549

Access Control: Publicly Available

 

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