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Picking the Amateur’s Mind – Predicting Chess Player Strength from Game Annotations Christian Scheible Institute for Natural Language Processing University of Stuttgart, Germany
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Document Date: 2014-08-08 12:19:49


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City

Dublin / /

Company

Neural Information Processing Systems / Chess Enterprises / Wilson / Creative Commons / /

Country

Ireland / /

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Facility

Natural Language Processing University of Stuttgart / Language Processing University of Munich / Game Annotations Christian Scheible Institute / /

IndustryTerm

spoken dialogue systems / downstream applications / online reviews / web resources / natural language processing / /

MedicalCondition

MS / /

Organization

Hinrich Schutze Center for Information / Natural Language Processing University of Stuttgart / Game Annotations Christian Scheible Institute / Information and Language Processing University of Munich / Association for Computational Linguistics / /

Person

Jason Utt / Roberta Calderwood / Xiangji Huang / David L Chen / Steven J Edwards / Yang Liu / Eric W Noreen / Farah Benamara / Dries Verdegem / Xiaohui Yu / Ralf Herbrich / Chung Chang / Pascal Francq / Kyle Richardson / David Silver / Beth W Crandall / Alexander Panchenko / Hugues Bersini / Tatsuya Kawahara / Alex Lascarides / Aijun An / Martin D Murphy / Alfred A Cleveland / Anais Cadilhac / Thore Graepel / Jen Lin / Marco Saerens / Daniel Quernheim / Dan Heisman / Kazunori Komatani / Gary A Klein / Adrien Dessy / Douglas Pfau / Klaus Obermayer / Nicholas Asher / Raymond J Mooney / Shinichi Ueno / Strength / Hiroshi G. Okuno / Regina Barzilay / /

Position

queen / speaker / Chess Player / Commentator / player / good player / dark-square bishop / king / bishop / Moved bishop / writer / light-square bishop / /

PublishedMedium

The American Journal of Psychology / Computational Linguistics / /

SportsGame

chess / /

Technology

machine learning / Natural Language Processing / Data Mining / /

URL

http /

SocialTag