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Named Entity Recognition in Tweets: An Experimental Study
The novel T-ner system doubles F1 score compared with the Stanford NER system, and leverages the redundancy inherent in tweets to achieve this performance, using LabeledLDA to exploit Freebase dictionaries as a source of distant supervision. Expand
Open domain event extraction from twitter
TwiCal is described-- the first open-domain event-extraction and categorization system for Twitter, and a novel approach for discovering important event categories and classifying extracted events based on latent variable models is presented. Expand
Twitter Part-of-Speech Tagging for All: Overcoming Sparse and Noisy Data
A novel approach to system combination for the case where available taggers use different tagsets, based on voteconstrained bootstrapping with unlabeled data, reaches 88.7% tagging accuracy, a new high in PTB-compatible tweet part-of-speech tagging. Expand
SwatCS: Combining simple classifiers with estimated accuracy
This paper is an overview of the SwatCS system submitted to SemEval-2013 Task 2A: Contextual Polarity Disambiguation, using a combination of classifiers trained on a range of lexical features. Expand
Understanding YouTube Communities via Subscription-based Channel Embeddings
New methods to discover and classify YouTube channels which enable the analysis of communities and categories on the platform using orders of magnitude more channels than have been used in previous studies are presented. Expand
Genre Classification Using Machine Learning Techniques
Music is categorized into subjective categories called genres. Humans have been the primary tool in attributing genre-tags to songs. Using a machine to automate this classification process is a moreExpand
"Penrod" and the Perception of Characters in Blackface at UW-Eau Claire
The purpose of this project is to examine the multiple components of minstrel shows that were performed annually at UW-Eau Claire during the late 1920s and early 1930s, as well as other theatricalExpand