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Effectiveness of Domain Adaptation Approaches for Social Media PoS Tagging

We compare a comprehensive list of domain adaptation approaches for PoS tagging of social media data. We find that the most effective approach is based on clustering of unlabeled data. We also show that combining different approaches does not further improve performance. Thus, PoS tagging of social media data remains a challenging problem.

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Conference:
Second Italian Conference on Computational Linguistics CLiC-it 2015, 3-4 December 2015, Trento
Date Issued:
2015
URN:
urn:nbn:de:hbz:464-20211022-122109-1
DOI:
10.4000/books.aaccademia.1494
Language:
English
Type of Resource:
Text
Collection:
E-Publications
Subject categories of the Deutsche Nationalbibliografie:
004 Data processing Computer sciences
Hosting institution:
Faculty of Engineering, Computer Science and Applied Cognitive Science, Computer Science, Language Technology Lab
Info on primary publication:
Horsmann, T., & Zesch, T. (2015). Effectiveness of Domain Adaptation Approaches for Social Media PoS Tagging. In: Bosco, C., Tonelli, S., & Zanzotto, F. M. (Eds.) Proceedings of the Second Italian Conference on Computational Linguistics CLiC-it 2015 : 3-4 December 2015, Trento, pp. 166-170. Torino : Accademia University Press. doi: 10.4000/books.aaccademia.1494

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