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RPosition Statement?attendingFamilyGivenJob titleCompanyWeb industry?Localisation industry?Email21/03/2013lunch for 21/03/14VegetarianDiet Notesdon´t want to be in announcement listdon´t give permission for contact infoRegistration ConfirmationNotesBelong to LIDERFinancial Support
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111BenjaminMartinExecutive Director/ Senior ScientistKamusi Project International/ EPFL martin.benjamin@epfl.ch111I eat seafood, but nothing that breathes air (no chicken, no meat).001000Kamusi is an open multilingual concept-based lexical platform, for use by
people and by machine applications, that is capable of producing and
interlinking rich linguistic data for every word in every language.

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101BezgachevaJuliaData Scentist/Open Data SpecialistWorld Bank jbezgacheva@worldbank.org110000100
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101BordeaGeorgetaPostdoctoral ResearcherInsight, Centre for Data Analytics, NUI Galway, Ireland georgeta.bordea@deri.org110001100
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101CalzolariNicolettaILC-CNR glottolo@ilc.cnr.it1110001000
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101Callahan JohnAssociate DirectorONR Globaljcallahan@acm.org1000111000
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101CimianoPhilippProfUniversity of Bielefeld / CITECcimiano@cit-ec.uni-bielefeld.de1110001
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111KernermanIlanCEOK Dictionariesilan@kdictionaries.com1100011000Developing multi-language dictionary-driven data for NLP application
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101KoidlKevinResearch FellowTrinity College Dublin

1kevin.koidl@scss.tcd.ie1100001000
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101FragkouPavlinaProgrammerInformation Development Agencyfragou@iit.demokritos.gr100000100
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101Georgakopoulou Dr. Yota Sr Director, Research & Int’l DevelopmentDeluxe1yota.georgakopoulou@bydeluxe.com110000100
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101Gialama Maria Account ManagerDeluxe1maria.gialama@bydeluxe.com110000100
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101GiouliVoula ResearcherInstitute for Language and Speech Processing, R.C. "Athena"voula@ilsp.athena-innovation.gr110000100
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101Gómez-PerezAsunciónFull ProfessorUniversidad Politécnica de Madridasun@fi.upm.es110000101
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111GornostayTatiana Terminology service manager, Business Development managerTilde1tatiana.gornostay@tilde.lv111000100Towards Cooperation of Terminology resources and Linked Open Data

Challenge: interoperability of terminology resources and linked open data,
multilinguality, emerging domains. Idea: a standardised approach to
representation of terminology resources in the linked open data format,
win-win cooperation between terminology resources and services and linked
open data resources and services. I will present a use case of and lessons
learnt from creating a Web-based platform for multilingual terminology
services for the European official languages. I call for cooperation and
joint initiatives to overcome main obstacles: availability, fragmentation,
and consistency of resources and services.
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101GraciaJorgePostdoctoral ResearcherUniversidad Politécnica de Madrid (UPM)jgracia@fi.upm.es110000101
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101MagnusdottirGudrunCSOESTeam AB1gudrun@esteam.se110000100
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101MarkantonatouStellaComputational LinguistILSP/RIC Athenastellamarkantonatou@yahoo.com110000100
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101MarcianteGiuseppeChief Excutive OfficerBusiness Innovation Companyg.marciante@gmail.com1000010
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111McCraeJohnResearch AssociateUniversity Bielefeldjmccrae@cit-ec.uni-bielefeld.de11000100Linked data to connect lexical resources: the case of WordNets
In this talk I will discuss the topic of how we can use linked data to connect language resources
across multiple languages and domains. In particular, here I will focus on the case of WordNets,
which have been created for not only English but also over 100 other languages. However, the
creation of these resources has not be well-coordinated and these resources use nearly as
many distinct formats and linking mechanisms as there are resources. Furthermore, the linking has
been further exacerbated by the lack of a common identifier scheme for linking. I will present
the relevant issues and how we have aimed to solve it by working to create a linked data version of
the Princeton WordNet using RDF and lemon.
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101Mcguire John-KinfundJohn@kinfund.ie110000100
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101Mouzakitis SpirosResearcherNational Technical University of Athensmouzakitis.epu@gmail.com110001100
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111NadalisCostasLocalisation Technical ConsultantTMServeCostasNadalis@TMServe.gr110000100The Need for Clean Language Data and the Rules for Cleaning it.

Over the last 30 years a significant amount of language data in the form of bilingual or multilingual text (translation memories or glossaries), has been collected. These data, however, is usually stored in proprietary formats together with language irrelevant information aimed to serve translation needs and specific tool functionalities. During the recent years, primarily due to the increase in the usage of Machine Translation (MT), there is an increasing need in cleaning up these language resources and make them appropriate for training data for MT systems. Some of the main cleaning steps will be presented and the need for appropriate rules and tools will be addressed.
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101NavigliRoberto Associate ProfessorSapienza University of Romenavigli@di.uniroma1.it11100011
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101PapageorgiouHarrisResearcherATHENA RC xaris@ilsp.athena-innovation.gr1110001
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101PetasisGeorgiosAssociate ResearcherNCSR "Demokritos" petasis@iit.demokritos.gr110000100
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101PetychakisMichael Research AssistantNational Technical University of Athensmpetyx@epu.ntua.gr110000100
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101PilouDespina Senior Project CoordinatorTexto - Lexikopoleio - Translation & Publishing Ltd1prod@texto.gr100000100
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101PiperidisStelios ILSP / ATHENA RCspip@ilsp.gr100000100
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111RitchiePhilCTOVistaTEC1philr@vistatec.ie1100010My company does translation of a lot of marketing content. We have some
documented style guides and branding guidelines but we are interested in
the possibilities of modelling these concepts using linked data and
inferencing. For example, we would like to see if the types of metaphor,
affective messaging and conceptual portrayal can be encoded. The goal if
this is possible would be to have automation which, given source content,
could suggest localized emotive phrasing.

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101SasakiFelixSenior ResearcherDFKI / W3C Fellowfsasaki@w3.org110000101
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101ScharlArnoManaging Director webLyzard technology1 scharl@weblyzard.com110000100
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101SimovKiril Associate ProfessorBulgarian Academy of Scienceskivs@bultreebank.org110010100
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111StoitsisGiannis Chief Technology OfficerAgro-Know1stoitsis@ieee.org110001100Best practices and open source tools for expanding the multilinguality of
online services
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101TreinenWolfgangPolicy and Project OfficerEuropean Commissionwolfgang.treinen@ec.europa.eu1000001Due to another meeting in the morning, I will only attend the afternoon
session (probably from 14.00 / 14.30 h onwards)
0
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101Uszkoreit HansDFKIhans.uszkoreit@dfki.de110000000
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111VakaliAthenaProfessorInformatics Dept, Aristotle Universityavakali@csd.auth.gr1100001probably can make it only for morning sessions0Looking into pathways from Social Web to the Web of Linked Data - we've
worked on a framework as a pathway to (a) identify
important patterns in Social Web, (b) enrich the identified patterns with
relevant formal descriptions already in the web, and (c) generate machine
understandable formal descriptions for the identified patterns, which can
be further exploited by services.
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111Vila-SueroDanielResearcherOntology Engineering Group, UPM
dvila@fi.upm.es110000101?
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101VulcuGabriela Research Associate Insight, Centre for Data Analytics, NUI Galway, Irelandgabriela.vulcu@deri.org110000100
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101XuFeiyuSenior ResearcherDFKI feiyu@dfki.de110000100
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Not registered but attending
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1MilosevicUros
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Cancelled
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1BuitelaarPaulSenior Research FellowINSIGHT, National University of Ireland, Galway paul.buitelaar@deri.org1100001000
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111BrancoAntónioResearcherUniversity of LisbonAntonio.Branco@di.fc.ul.pt110000100In the last decade, the incremental advancement of mainstream research on Machine Translation (MT) has been obtained by encompassing increasingly sophisticated statistical approaches and fine-grained linguistic features that add to thesurface level alignment on which thes approaches are ultimately anchored.
The goal of our QTLeap project is to contribute to a decisive push in quality MT by pursuing a novel approach that opens the way to higher quality translations and a new cycle of technological advancement.

The construction of Linked Open Data and other semantic resources has progressed now to support impactful application of lexical semantic processing that handles and resolves referential and conceptual ambiguity.

The construction of deep treebanks, in turn, has progressed to be delivering now the first significant Parallel DeepBanks, where pairs of synonymous sentences from different languages are annotated with their fully-fledged grammatical representations, up to the level of their semantic representation.

These cutting edge advances permit for the cross-lingual alignment supporting translation to be established at the level of deeper linguistic representation. The deeper the level the less language-specific differences remain among source and target sentences and new chances of success become available for the statistically based transduction
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111KordoniValiaResearch ProfessorHumboldt-Universität zu Berlin, Germanykordonie@anglistik.hu-berlin.de

11000010https://drive.google.com/?authuser=0#folders/0B6L1GIK9dcoCTmRWRmdsRHNVUlk
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Could not be contacted
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11Damova MarianaCEOMozaika?110000100Language resources as Linked Data. WE CAN NOT CONTACT HER. EMAIL ADDRESS IS NOT RIGHT
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