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Cfp - Mining Big Text Data for Semantics (M4S)

From: Boris Marcelo Villazon Terrazas <boris.villazon.terrazas@gmail.com>
Date: Sat, 7 May 2016 14:06:01 +0200
Message-ID: <CAJ9EsGLM5Q+3x63Sj-M-0WMxgMQuuBgbrpJWBbvcTBLRXNtLFg@mail.gmail.com>
To: public-semweb-lifesci@w3.org
*Mining Big Text Data for Semantics (M4S)*



and it applications in Finance and Healthcare







ISWC workshop, October 2016, Kobe Japan,







http://www.pitt.edu/~dah44/M4S-2016/M4S







The Mining Big Text Data for Semantics (M4S) workshop aims to explore the



potential combinations of statistical and formal semantic based approaches



that will help to combine the analytic depth and precision of the latter



with the scalability, recall and speed of the former.







M4S focuses on two application domains, namely healthcare and finance. For



both, we see coexistence of large amount of textual documents, which are



still the predominant means of communication, and extensive models in
formal



knowledge representation languages. Taking healthcare as an example,
textual



documents are still the means of communication when scholars, industrial



practitioners, and authorities publish their research findings, clinical
trial



reports, recommendations, GxP protocols and guidelines. However, gigantic



ontologies are also widely available as the outcomes of community-wide



collaborations. In the finance domain, new pieces of data are being
produced



at second or even millisecond magnitude. Unambiguously defining the data
nuances



and bringing them under regulatory powers of authorities becomes essential.







The workshop intends to foster discussions and seek answers to the
following



research and development questions:







Theoretical questions



  1. How can distributional semantics and formal semantic work seamlessly



     together?



  2. What is the optimal way of combining e.g. large-scale curated
knowledge



     models with associations mined from large text corpora?



  3. Which characteristics of formal knowledge models are needed such that



     they can be used in combination with distributional semantics?







Application questions



  1. How do certain NLP tasks benefit from a combination of distributional



     and formal semantics?



  2. Specifically, how can such combination be used fruitfully in the



     healthcare and finance domains?







**Topics**







Topics of interest include but are not limited to:







Learning/mining formal semantics from large text corpora



  1. Relation mining, extraction and validation



  2. Event extraction



  3. Entity disambiguation and resolution



  4. Latent topic modelling



  5. Incorporate imperfections from text mining in semantic web







Working with two sorts of semantics



  1. Ontology enhanced distributional language models



  2. Reasoning with both distributional and formal semantics



  3. Full-text search: increasing precision and recall of searches using
semantics



  4. Semantics-based information extraction,



  5. Question answering



  6. Translation aids and Multilingual systems







Utilisation in finance and healthcare



  1. Requirements and use cases



  2. Technical and business challenges







Deployed systems



  1. Mining from open data such as PubMed, Edgar, OpenFDA, etc.



  2. Experiences and lessons-learnt,



  3. Evaluation results







**Submission and Proceedings**







M4S invites three types of submissions:



  1. Technical papers: maximum 14 pages



  2. Short position papers: maximum 6 pages



  3. System demo: a 2-page summary of system features







Submitted papers will be peer-reviewed by at least two workshop Programme



Committee members. Accepted papers will be presented at the workshop. All



papers should be written in English following the Springer conference
proceedings



format. Technical papers should not exceed 14 pages including bibliography
and



figures. Short position papers should be no more than 6 pages clearly state



position paper in the title. All system demo submissions should be
accompanied



by a two-page description of key features and core technologies of the
system.



Preferably, a link to the real demo should be made available at the time of
submission.







**Important Dates**







Paper submission due        Sunday, 10 July 2016



Author notification   Sunday, 31 July 2016



Camera ready copy due      Sunday, 21 August 2016







**Program Committee**







Panos Alexopoulus                          TextKernel, Netherlands



Ghislain Atemezling                         Mondeca, France



Christian Biemann                           TU Darmstadt, Germany



Victor de la Torre                             Fujitsu Laboratories of
Europe, Spain



Ronald Denaux                                 Expert System, Spain



Jana Diesner                                     UIUC, USA



Sergio Fernanadez                           Redlink, Austria



Alessio Ferrari                                  ISTI CNR, Italy



Nuria Garcia-Santa                          Expert System, Spain



Andreas Holzinger                           TU Graz, Austria



Daqing He                                         Pittsburgh University, USA



Gerhard Heyer                                 University of Leipzig, Germany



Bo Hu                                                Fujitsu, United Kingdom



Terunobu Kume                              Fujitsu Labs, Japan



Yu-ru Lin                                          Pittsburgh University,
USA



Nuno Lopez                                      IBM, Ireland



Pablo Mendes                                   IBM, USA



Fumihito Nishino                             Fujitsu, Japan



Vandenbussche Pierre-Yves          Fujitsu, Ireland



Elena Montiel Ponsoda                   UPM, Spain



Simone Paolo Ponzetto                   University of Mannheim, Germany



Angus Roberts                                 University of Sheffield, UK



Barbara Thnssen                             FHNW, Switzerland



Boris Villazon Terrazas                   Fujitsu Laboratories of Europe,
Spain



Hans Friedrich Witschel                 FHNW, Switzerland
Received on Saturday, 7 May 2016 12:06:30 UTC

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