Three papers accepted at LREC 2014: "CROMER: A Tool for Cross-Document Event and Entity Coreference", "Crowdsourcing for the identification of event nominals: an experiment", "A SICK cure for the evaluation of compositional distributional semantic models".
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The proposal "Creating a platform for navigating verbo-visual art collections" by Sara Tonelli and Rachele Sprugnoli has been accepted at "Museums and the Web 2014" conference in Florence. You can find the abstract here.
Extended abstract and slides presented at the AIUCD Annual Conference 2013 in Padua are online: http://dh.fbk.eu/news/paper-accepted-aiucd-annual-conference-2013
The paper "Classifying Temporal Relations with Simple Features" by Paramita Mirza and Sara Tonelli has been accepted at the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL2014).
Slides of our ""Digital Humanities: Current state and Future challenges" workshop in memory of Emanuele Pianta are now available: https://dh.fbk.eu/events/dh-workshop-memory-emanuele-pianta
The poster presented at the Herrenhausen Conference "(Digital) Humanities Revisited – Challenges and Opportunities in the Digital Age" in Hanover is available online
Twitter stream and pictures of the DH Workshop in Memory of Emanuele Pianta are available online: https://dh.fbk.eu/events/dh-workshop-memory-emanuele-pianta
The paper "The Verbo-Visual Virtual Platform for Digitizing and Navigating Cultural Heritage Collections" by Alessandro Marchetti and Sara Tonelli has been accepted at the 2nd AIUCD Annual Conference on Collaborative Research Practices and Shared Infrastructures for Humanities Computing [Download extended abstract here].
During the final review of the Terence European Project, in which the DH group was involved for the language analysis and simplification task, the project outcome has been rated as "excellent". Congratulations to all the Consortium partners!
Stefano Menini is among the organizers of SemEval 2014 task on "Evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment".