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Named Entity Recognition: Adapting to Microblogging
| Citations: | 12 - 0 self |
BibTeX
@MISC{Locke_namedentity,
author = {Brian Locke and Dr. James Martin Ph. D},
title = {Named Entity Recognition: Adapting to Microblogging},
year = {}
}
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Abstract
In this project, we seek to create a Named Entity Recognizer (NER) tuned for use on Twitter posts. We will be identifying Named Entities and classifying them as People, Locations, or Organizations. We hope to identify language features and methods that effectively transfer the techniques and knowledge from Named Entity Recognition research on formal sources, such as news articles, to less structured microblogging texts. In the process, we will identify differences between microblogging text and formal prose which are relevant to NER. 1.1 Summary There has been much research in Named Entity Recognition on news articles. However, many applications of NER, and Natural Language Processing in general, involve analyzing data that is less structured, such as blog posts, instant messages, and movie reviews. In our project, we will attempt to create a classifier that performs NER on microblog postings. In doing so, we hope to explore approaches to transferring learning from a domain with more data available to one with less.
Keyphrases
entity recognition news article language feature twitter post formal prose many application blog post instant message movie review named entity recognizer much research structured microblogging text microblog posting named entity named entity recognition natural language processing entity recognition research formal source
