📰 Workshop on Noisy User-generated Text 2016 — accepted papers

Workshop on Noisy User-generated Text 2016 is the 2016 edition of the Workshop on Noisy User-generated Text, held in Osaka, Japan, December 2016 (publisher: Association for Computational Linguistics). OpenAlex lists 31 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Osaka, Japan · 🗓 December 2016

All accepted papers (31)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. A Simple Scalable Neural Networks based Model for Geolocation Prediction in Twitter ↗Yasuhide Miura, Motoki Taniguchi, Tomoki Taniguchi et al.
2. A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine TranslationMarlies van der Wees, Arianna Bisazza, Christof Monzour summary
3. ASU: An Experimental Study on Applying Deep Learning in Twitter Named Entity Recognition. ↗Michel Naim Gerguis, Cherif Salama, M. Watheq El-Kharashi
4. Analysis of Twitter Data for Postmarketing Surveillance in Pharmacovigilance ↗Julie Pain, Jessie Levacher, Adam Quinquenel et al.
5. Bidirectional LSTM for Named Entity Recognition in Twitter Messages ↗Nut Limsopatham, Nigel Collier
6. CSIRO Data61 at the WNUT Geo Shared Task ↗Gaya Jayasinghe, Brian Jin, James Mchugh et al.
7. DISAANA and D-SUMM: Large-scale Real Time NLP Systems for Analyzing Disaster Related Reports in Tweets ↗Kentaro Torisawa
8. DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets ↗Fabrice Dugas, Eric Nichols
9. Disaster Analysis using User-Generated Weather Report ↗Yasunobu Asakura, Masatsugu Hangyo, Mamoru Komachi
10. Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalization ↗Thales Felipe Costa Bertaglia, Maria das Graças Volpe Nunes
11. Feature-Rich Twitter Named Entity Recognition and Classification ↗Utpal Kumar Sikdar, Björn Gambäck
12. From Entity Linking to Question Answering – Recent Progress on Semantic Grounding Tasks ↗Ming-Wei Chang
13. From Noisy Questions to Minecraft Texts: Annotation Challenges in Extreme Syntax Scenario ↗Héctor Martínez Alonso, Djamé Seddah, Benoît Sagot
14. Geolocation Prediction in Twitter Using Location Indicative Words and Textual Features ↗Lianhua Chi, Kwan Hui Lim, Nebula Alam et al.
15. How Document Pre-processing affects Keyphrase Extraction Performance ↗Florian Boudin, Hugo Mougard, Damien Cram
16. Japanese Text Normalization with Encoder-Decoder Model ↗Taishi Ikeda, Hiroyuki Shindo, Yuji Matsumoto
17. Learning to Search for Recognizing Named Entities in Twitter ↗Ioannis Partalas, Cédric Lopez, Nadia Derbas et al.
18. Learning to recognise named entities in tweets by exploiting weakly labelled data ↗Kurt Junshean Espinosa, Riza Theresa Batista-Navarro, Sophia Ananiadou
19. Name Variation in Community Question Answering Systems ↗Anietie Andy, Satoshi Sekine, Mugizi Rwebangira et al.
20. Named Entity Recognition and Hashtag Decomposition to Improve the Classification of Tweets ↗Billal Belainine, Alexsandro Fonseca, Fatiha Sadat
21. Private or Corporate? Predicting User Types on Twitter ↗Nikola Ljubešić, Darja Fišer
22. Processing non-canonical or noisy text: fortuitous data to the rescue ↗Barbara Plank
23. Results of the WNUT16 Named Entity Recognition Shared Task ↗Benjamin Strauss, Bethany Toma, Alan Ritter et al.
24. Semi-supervised Named Entity Recognition in noisy-text ↗Shubhanshu Mishra, Jana Diesner
25. Topic Stability over Noisy Sources ↗Jing Su, Derek Greene, Oisín Boydell

See all 31 papers in Workshop on Noisy User-generated Text 2016 — accepted papers →

📄 Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine TranslationWorkshop on Noisy User-generated TextMarlies van der Wees, Arianna Bisazza, Christof Monz2016 · 18 citations
2. Unsupervised Stemmer for Arabic TweetsWorkshop on Noisy User-generated TextFahad Albogamy, Allan Ramsay2016 · 8 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

Semitic languages (2)🔁Machine translation (1)🧩Morphology (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓University of ManchesterManchester · United Kingdom1 work here🎓University of AmsterdamAmsterdam · Netherlands1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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