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CICLing 2016

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A presentation about the 17th International Conference on Intelligent Text Processing and Computational Linguistics in Konya, Turkey, April 3 - 9, 2016

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CICLing 2016

  1. 1. CICLing 2016 17th International Conference on Intelligent Text Processing and Computational Linguistics Konya, Turkey April 3 – 9, 2016
  2. 2. Conference
  3. 3. Mevlana University • Funded in 2009 • Rebuilt from a shopping mall • Wants to partner-up with other universities
  4. 4. CICLing 2016 Statistics • 206 accepted papers • 88 for Springer Lecture Notes in Computer Science • 20 for Journal Computación y Sistemas • 12 for Journal Polibits • 20 for International Journal of Computational Linguistics and Applications • 24 for IEEE CPS proceedings of ACLing (only papers on Arabic language) • 13 for IEEE CPS proceedings of TurCLing (only papers on Turkic languages) • 29 for Journal Research in Computing Science
  5. 5. CICLing 2016 Statistics • 157 attended • 43 with a CICLing oral presentation • 38 with a ACLing or TurCLing oral presentation • 76 with a poster for CICLing, ACLing or TurCLing
  6. 6. CICLing 2016 Facts • You are a professor! • CICLing has no sponsors • CICLing has no backing organization • CICLing costs more than other conferences • CICLing has 3 full-day excursions
  7. 7. CICLing 2016 Quotes • «Some poster presenters came without a poster, because only the one minute long presentation about the poster was important, so that they can say that they gave a presentation at the conference» • «Do you use Theano? No, I don`t have access to GPUs» • «We use available parallel corpora which is becoming increasingly available» • «RNNs are chosen for the wrong reasons: easier to get a paper published»
  8. 8. Keynotes
  9. 9. A Roadmap towards Machine Intelligence Tomas Mikolov, Facebook Research Recurrent networks and beyond • RNNs are chosen for the wrong reasons: easier to get a paper published • Optimize not how good something can be learned, but how fast something new can be learned with as little as possible teaching • https://www.youtube.com/watch?v=FUlTjKL-mVA
  10. 10. NewsReader: a machine for reading massive streams of news to generate event-centric knowledge graphs Piek Vossen, University Amsterdam
  11. 11. Discussion about reproducible results and publishing of code and data • Scientists need to advance science • Not just them selves • Negative results should also be published whet possible
  12. 12. Deeper summarisation: the second time around. An overview and some practical suggestions Simone Teufel, University of Cambridge
  13. 13. Robots With Heart Pascale Fung, Hong Kong University of Science and Technology • «Some people just like to abuse robots» • Humor is • Setup • Trigger • Punchline • Robotics people study dancers to learn how to express emotion through motion
  14. 14. Discussion about robots How to make future robots and humans get along • Reward them for good work like children • Be good ourselves so that they learn good examples • Keep some kind of backup stop or self-destruct button • Hardcode only because robots that can learn are too dangerous
  15. 15. Presentations
  16. 16. Generating Bags of Words from the Sums of their Word Embeddings Lyndon White, Roberto Togneri, Wei Liu and Mohammed Bennamoun Best student paper • NP-Hard problem • Using a greedy algorithm to convert the vector to a bag of words • Part-way step towards generating full sentences
  17. 17. Pluralising Nouns in isiZulu and Related Languages Joan Byamugisha, C. Maria Keet and Langa Khumalo
  18. 18. Pluralising Nouns in isiZulu and Related Languages Joan Byamugisha, C. Maria Keet and Langa Khumalo
  19. 19. Enabling Medical Translation for Low-Resource Languages Ahmad Musleh, Nadir Durrani, Irina Temnikova, Preslav Nakov, Stephan Vogel and Osama Alsaad • Data Collection • Wiki Dumps • Wikipedia • Wiktionary • OmegaWiki • Doctor-Patient YouTube Videos and Movie Subtitles • OCR • Translated into Hindi using Google Translate, and post-edited by a Hindi native speaker • BabelNet and MeSH • extracted medical terms from BabelNet • Medical Subject Headings • Data Synthesis
  20. 20. Enabling Medical Translation for Low-Resource Languages Ahmad Musleh, Nadir Durrani, Irina Temnikova, Preslav Nakov, Stephan Vogel and Osama Alsaad • +3.11 BLEU points absolute for English-to-Hindi • +2.07 for Hindi-to-English • In future work • collect more data for Hindi, but also to synthesize Urdu data • develop a system for Nepali-English • add Automatic Speech Recognition (ASR) and Speech Synthesis components in order to build a fully-functional speech-to-speech system
  21. 21. Posters http://ej.uz/cicling2016posters
  22. 22. WebBrain: Joint Neural Learning of Large-Scale Common Sense
  23. 23. Emerging Technology Enabling Dyslexia Users To Read and Perceive Written Text Correctly Best Poster
  24. 24. Instant Translation Model Adaptation by Translating Unseen Words in Continuous Vector Space The method exploits a projection of semantic representations of OOV words in the source-language onto the target-language semantic space to look for translation candidates for the OOV words
  25. 25. Photos https://www.instagram.com/m4t1ss/

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