Paper Info
Title
Fine-Grained POS Tagging of German Social Media and Web Texts.
Abstract
This paper presents work on part-of-speech tagging of German social media and web texts. We take a simple Hidden Markov Model based tagger as a starting point, and extend it with a distributional approach to estimating lexical (emission) probabilities of out-of-vocabulary words, which occur frequently in social media and web texts and are a major reason for the low performance of off-the-shelf taggers on these types of text. We evaluate our approach on the recent EmpiriST 2015 shared task dataset and show that our approach improves accuracy on out-of-vocabulary tokens by up to 5.8%; overall, we improve state-of-the-art by 0.4% to 90.9% accuracy.
Year
DOI
Venue
2017
10.1007/978-3-319-73706-5_7
Lecture Notes in Artificial Intelligence
DocType
Volume
ISSN
Conference
10713
0302-9743
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Stefan Thater175638.54