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NUT@COLING 2016: Osaka, Japan
- Bo Han, Alan Ritter, Leon Derczynski, Wei Xu, Tim Baldwin:

Proceedings of the 2nd Workshop on Noisy User-generated Text, NUT@COLING 2016, Osaka, Japan, December 11, 2016. The COLING 2016 Organizing Committee 2016 - Barbara Plank:

Processing non-canonical or noisy text: fortuitous data to the rescue. 1 - Ming-Wei Chang:

From Entity Linking to Question Answering - Recent Progress on Semantic Grounding Tasks. 2 - Kentaro Torisawa:

DISAANA and D-SUMM: Large-scale Real Time NLP Systems for Analyzing Disaster Related Reports in Tweets. 3 - Nikola Ljubesic, Darja Fiser:

Private or Corporate? Predicting User Types on Twitter. 4-12 - Héctor Martínez Alonso, Djamé Seddah, Benoît Sagot:

From Noisy Questions to Minecraft Texts: Annotation Challenges in Extreme Syntax Scenario. 13-23 - Yasunobu Asakura, Masatsugu Hangyo, Mamoru Komachi:

Disaster Analysis using User-Generated Weather Report. 24-32 - Uwe D. Reichel, Piroska Lendvai:

Veracity Computing from Lexical Cues and Perceived Certainty Trends. 33-42 - Marlies van der Wees, Arianna Bisazza, Christof Monz:

A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation. 43-50 - Anietie Andy, Satoshi Sekine, Mugizi Rwebangira, Mark Dredze:

Name Variation in Community Question Answering Systems. 51-60 - Wei-Chung Wang, Hung-Chen Chen, Zhi-Kai Ji, Hui-I Hsiao, Yu-Shian Chiu, Lun-Wei Ku:

Whose Nickname is This? Recognizing Politicians from Their Aliases. 61-69 - Ajit Jain, Girish Kasiviswanathan, Ruihong Huang:

Towards Accurate Event Detection in Social Media: A Weakly Supervised Approach for Learning Implicit Event Indicators. 70-77 - Fahad R. Albogamy, Allan Ramsay:

Unsupervised Stemmer for Arabic Tweets. 78-84 - Jing Su, Derek Greene, Oisín Boydell:

Topic Stability over Noisy Sources. 85-93 - Julie Pain, Jessie Levacher, Adam Quinquenel, Anja Belz:

Analysis of Twitter Data for Postmarketing Surveillance in Pharmacovigilance. 94-101 - Belainine Billal, Alexsandro Fonseca, Fatiha Sadat:

Named Entity Recognition and Hashtag Decomposition to Improve the Classification of Tweets. 102-111 - Thales Felipe Costa Bertaglia, Maria das Graças Volpe Nunes:

Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalization. 112-120 - Florian Boudin, Hugo Mougard, Damien Cram:

How Document Pre-processing affects Keyphrase Extraction Performance. 121-128 - Taishi Ikeda, Hiroyuki Shindo, Yuji Matsumoto:

Japanese Text Normalization with Encoder-Decoder Model. 129-137 - Benjamin Strauss, Bethany Toma, Alan Ritter, Marie-Catherine de Marneffe, Wei Xu:

Results of the WNUT16 Named Entity Recognition Shared Task. 138-144 - Nut Limsopatham, Nigel Collier:

Bidirectional LSTM for Named Entity Recognition in Twitter Messages. 145-152 - Kurt Junshean Espinosa, Riza Theresa Batista-Navarro, Sophia Ananiadou:

Learning to recognise named entities in tweets by exploiting weakly labelled data. 153-163 - Utpal Kumar Sikdar, Björn Gambäck:

Feature-Rich Twitter Named Entity Recognition and Classification. 164-170 - Ioannis Partalas, Cédric Lopez, Nadia Derbas, Ruslan Kalitvianski:

Learning to Search for Recognizing Named Entities in Twitter. 171-177 - Fabrice Dugas, Eric Nichols:

DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets. 178-187 - Michel Naim Gerguis, Cherif R. Salama, M. Watheq El-Kharashi:

ASU: An Experimental Study on Applying Deep Learning in Twitter Named Entity Recognition. 188-196 - Ngoc Tan Le, Fatma Mallek, Fatiha Sadat:

UQAM-NTL: Named entity recognition in Twitter messages. 197-202 - Shubhanshu Mishra, Jana Diesner:

Semi-supervised Named Entity Recognition in noisy-text. 203-212 - Bo Han, Afshin Rahimi, Leon Derczynski, Timothy Baldwin:

Twitter Geolocation Prediction Shared Task of the 2016 Workshop on Noisy User-generated Text. 213-217 - Gaya Jayasinghe, Brian Jin, James McHugh, Bella Robinson, Stephen Wan:

CSIRO Data61 at the WNUT Geo Shared Task. 218-226 - Lianhua Chi, Kwan Hui Lim, Nebula Alam, Christopher J. Butler:

Geolocation Prediction in Twitter Using Location Indicative Words and Textual Features. 227-234 - Yasuhide Miura, Motoki Taniguchi, Tomoki Taniguchi, Tomoko Ohkuma:

A Simple Scalable Neural Networks based Model for Geolocation Prediction in Twitter. 235-239

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