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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,


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

knowledge representation languages. Taking healthcare as an example,

documents are still the means of communication when scholars, industrial

practitioners, and authorities publish their research findings, clinical

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

at second or even millisecond magnitude. Unambiguously defining the data

and bringing them under regulatory powers of authorities becomes essential.

The workshop intends to foster discussions and seek answers to the

research and development questions:

Theoretical questions

  1. How can distributional semantics and formal semantic work seamlessly


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

     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 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

  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

format. Technical papers should not exceed 14 pages including bibliography

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

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

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

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

**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,

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,

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

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