noisy-text.github.io

COLING 2016 Workshop on Noisy User-generated Text (W-NUT)

2016 The 2nd Workshop on Noisy User-generated Text (W-NUT). December 11 2016, Osaka, Japan ( last year. We have received 27 main workshop submissions! We look forward to seeing you at COLING! Veracity Computing from Lexical Cues and Perceived Certainty Trends. Uwe Reichel and Piroska Lendvai. Name Variation in Community Question Answering Systems. Anietie Andy, Satoshi Sekine, Mugizi Rwebangira and Mark Dredze. WNUT 2017 will be co-located with EMNLP! The Ohio State University). The Ohio State University).

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COLING 2016 Workshop on Noisy User-generated Text (W-NUT) | noisy-text.github.io Reviews

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2016 The 2nd Workshop on Noisy User-generated Text (W-NUT). December 11 2016, Osaka, Japan ( last year. We have received 27 main workshop submissions! We look forward to seeing you at COLING! Veracity Computing from Lexical Cues and Perceived Certainty Trends. Uwe Reichel and Piroska Lendvai. Name Variation in Community Question Answering Systems. Anietie Andy, Satoshi Sekine, Mugizi Rwebangira and Mark Dredze. WNUT 2017 will be co-located with EMNLP! The Ohio State University). The Ohio State University).

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COLING 2016 Workshop on Noisy User-generated Text (W-NUT) | noisy-text.github.io Reviews

https://noisy-text.github.io

2016 The 2nd Workshop on Noisy User-generated Text (W-NUT). December 11 2016, Osaka, Japan ( last year. We have received 27 main workshop submissions! We look forward to seeing you at COLING! Veracity Computing from Lexical Cues and Perceived Certainty Trends. Uwe Reichel and Piroska Lendvai. Name Variation in Community Question Answering Systems. Anietie Andy, Satoshi Sekine, Mugizi Rwebangira and Mark Dredze. WNUT 2017 will be co-located with EMNLP! The Ohio State University). The Ohio State University).

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noisy-text.github.io

1

EMNLP 2017 Workshop on Noisy User-generated Text (W-NUT)

http://noisy-text.github.io//2017/index.html

2017 The 3rd Workshop on Noisy User-generated Text (W-NUT). September 7th, Copenhagen (at EMNLP. The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, web forums, online reviews, clinic records and language learner essays. This year, there will be two shared tasks - details to be announced. The University of Sheffield). The Ohio State University). The Ohio State University). The University of Melbourne). We seek submissions of.

2

ACL 2015 Workshop on Noisy User-generated Text (W-NUT)

http://noisy-text.github.io//2015/index.html

ACL 2015 Workshop on Noisy User-generated Text (W-NUT). July 31 2015, CNCC 303A. This workshop focuses on core Natural Language Processing tasks applied to noisy user-generated text, such as that found in social media, web forums, online reviews and language learner essays. The workshop will host two shared tasks. 1) Named Entity Recognition in Twitter and 2) Normalization of Noisy Text. We would like to thank the speakers, presenters and attendees for making WNUT-2015 a success ( printable poster. Abstr...

3

EMNLP 2017 Workshop on Noisy User-generated Text (W-NUT)

http://noisy-text.github.io//2017

2017 The 3rd Workshop on Noisy User-generated Text (W-NUT). September 7th, Copenhagen (at EMNLP. The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, web forums, online reviews, clinic records and language learner essays. This year, there will be two shared tasks - details to be announced. The University of Sheffield). The Ohio State University). The Ohio State University). The University of Melbourne). We seek submissions of.

4

Geolocation Prediction in Twitter

http://noisy-text.github.io/2016/geo-shared-task.html

Datasets and Evaluation Metric. Geolocation Prediction in Twitter. The shared task is presented as a multiclass classification problem: you will be given a list of mutually exclusive classes (e.g. metropolitan city centres). You will also be given training/dev data based on this class representation. Your goal is to predict the class label for each item in the test dataset. The shared task will be carried out on two levels:. Each user has a unique class label). Training: 1 million users. Release of train...

5

Named Entity Recognition in Twitter

http://noisy-text.github.io/2016/ner-shared-task.html

Named Entity Recognition in Twitter. Named entity recognition is one of the first steps in most IE pipelines. The diverse and noisy style of user-generated social media text presents serious challenges, however. Performance still lags far behind that on formal text genres such as newswire. The goal of this shared evaluation is to promote research on NER in noisy text and also help to provide a standardized dataset and methodology for evaluation. The shared competition is completed. Data available here.

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COLING 2016 Workshop on Noisy User-generated Text (W-NUT)

2016 The 2nd Workshop on Noisy User-generated Text (W-NUT). December 11 2016, Osaka, Japan ( last year. We have received 27 main workshop submissions! We look forward to seeing you at COLING! Veracity Computing from Lexical Cues and Perceived Certainty Trends. Uwe Reichel and Piroska Lendvai. Name Variation in Community Question Answering Systems. Anietie Andy, Satoshi Sekine, Mugizi Rwebangira and Mark Dredze. WNUT 2017 will be co-located with EMNLP! The Ohio State University). The Ohio State University).

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