Summary of GSCL 2013 international NLP conference in Germany
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Transcript of Summary of GSCL 2013 international NLP conference in Germany
Aaron L.-F. Han
NLP2CT meeting on 4th October, 2013
http://www.linkedin.com/in/aaronhan
Natural Language Processing & Portuguese-Chinese Machine Translation Laboratory
Department of Computer and Information Science
University of Macau
23rd-27th, September, Darmstadt, Germany
5 days: workshops + tutorials + main conference
205 registrations
Around 30% percent foreigners
42% acceptance rate for long paper
Delegates from around 20 countries
Main conference: long paper + short paper + Nectar paper + Demos
5 workshops (4 before conference + 1 after conference)
5 tutorials before conference
3 invited talks during 3 days main conference
Invited talk one: Distributed Wikipedia LDA
By Massimiliano Ciaramita, research scientist at Google Zurich
http://research.google.com/pubs/MassimilianoCiaramita.html
Recent work on the disambiguation problem
Based on a novel distributed inference and representation framework that builds on Wikipedia, Latent Dirichlet Allocation and pipelines of MapReduce.
Invited talk two: Multimodal Sentiment Analysis
By Rada Mihalcea, Associate Professor in University of North Texas, US
http://www.cse.unt.edu/~rada/
A method that integrates linguistic, audio, and visual features for the purpose of identifying sentiment in online videos
Describe a novel dataset consisting of videos collected from the social media website YouTube and annotated for sentiment polarity at both video and utterance level
Joint use of visual, audio, and textual features greatly improves over the use of only one modality at a time
Run evaluations on datasets in English and Spanish
Invited talk three: Big Data and Text Analytics
By Hans Uszkoreit, Professor at Saarland University & Scientific Director at the German Research Center for Artificial Intelligence (DFKI)
http://www.coli.uni-saarland.de/~hansu/
Text analytics is faced with rapidly increasing volumes of language data
Big language data are not only a challenge for language technology but also an opportunity for obtaining application-specific language models that can cope with the long tail of linguistic creativity
Such models range from statistical models to large rule systems
Using examples from relation/event extraction, illustrate the exploitation of large-scale learning data for the acquisition of application specific syntactic and semantic knowledge
Five tutorials:
How to Design Effective Visualizations for Natural Language Processing
The Practitioner's Cookbook for Linked Lexical Resources
Natural Language Processing for Historical Texts
Text Analysis and Mining for Digital Humanities
Natural Language Processing and Rule-based Information Extraction with UIMA
Phrase Tagset Mapping for French and English Treebanks and Its Application in Machine Translation Evaluation
Aaron L.-F. Han, Derek F. Wong, Lidia S. Chao, Yervant Ho, Shuo Li, Lynn Zhu. GSCL 2013. LNCS Vol. 8105, pp. 119-131. Springer-Verlag Berlin Heidelberg.
Open source tool: https://github.com/aaronlifenghan/aaron-project-hppr
A Study of Chinese Word Segmentation Based on the Characteristics of Chinese
Aaron L.-F. Han, Derek F. Wong, Lidia S. Chao, Yervant Ho, Lynn Zhu, Shuo Li. GSCL 2013, LNCS Vol. 8105, pp. 111-118. Springer-Verlag Berlin Heidelberg.
Aaron L.-F. Han
NLP2CT meeting on 4th October, 2013
http://www.linkedin.com/in/aaronhan
Natural Language Processing & Portuguese-Chinese Machine Translation Laboratory
Department of Computer and Information Science
University of Macau