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[CfP] Special Track on Knowledge Graph Construction and Consumption ICIW 2017

From: Sarasi Lalithsena <sarasi2010@gmail.com>
Date: Wed, 5 Apr 2017 14:41:45 -0400
Message-ID: <CAGVRkGn8vg5Jm1G8FRs-iv_svkhSnh6gHhNwDL7u84Vir9xhDg@mail.gmail.com>
To: semantic-web@w3.org
[Apologies if you receive this more than once]

Call for Papers

Special Track on Knowledge Graph Construction and Consumption (KGCC
<https://www.iaria.org/conferences2017/filesICIW17/KGCC.pdf>)

at ICIW 2017 <https://www.iaria.org/conferences2017/ICIW17.html> in Venice,
Italy

OVERVIEW

------------------------------------------

Over the past few years, Semantic Web and Artificial Intelligence research
community have a great interest in creating and consuming knowledge graphs.
This is further accelerated with the adoption of knowledge graphs by
industry giants such as Google, Bing, Yahoo and LinkedIn. These knowledge
graphs are being used for various applications such as question answering,
recommendation, document similarity/relevance, and knowledge discovery
covering variety of domains such as medical and healthcare, entertainment,
government and education.

Despite the wider adoption, creation and usage of knowledge graphs still
needs to tackle several challenges. Most of the existing usable knowledge
graphs are built with the human involvement and/or with structured data.
Currently, we have access to the ever growing unstructured and semi
structured data sources coming from different modalities and it is
essential to develop techniques that leverage the richness of these data
sources in creating knowledge graphs. This special track is focused on
discussing the challenges in creating knowledge graphs and also in
consuming knowledge graphs for various applications.

TOPICS OF INTEREST

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Topics include, but are not limited to, the following:

- Construction of knowledge graphs semi-automatically or automatically from
various heterogeneous multi-modal data sources; formal text, short text,
images, sensor data, etc

- Construct knowledge graphs for focused and specialized domains

- Structured machine learning on knowledge graphs

- Knowledge graph embedding in vector spaces

- Improve the quality of the knowledge graphs by dealing with the noise and
incompleteness of existing knowledge graphs

- Maintain the temporal relevancy of knowledge graphs; i.e., identify
emerging/fading concepts and facts

- Integration of knowledge graphs; alignment techniques to align classes,
relationships and instances

- Applications of leveraging knowledge graphs to improve the state of the
art techniques

- Scalability challenges in leveraging large knowledge graphs

CONTRIBUTION TYPES

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- Regular papers [in the proceedings, digital library]

- Short papers (work in progress) [in the proceedings, digital library]

- Posters: two pages [in the proceedings, digital library]

- Posters: slide only [slide-deck posted online]

- Presentations: slide only [slide-deck posted online]

- Demos: two pages [posted online]

IMPORTANT DATES

------------------------------------------

Submission deadline: May 17, 2017, Hawaii Time (GMT-10)

Contributions are to be submitted to the submission management system
<https://www.iariasubmit.org/conferences/submit/newcontribution.php?event=ICIW+2017+Special>
.

For more details, read the complete Call of Papers
<https://www.iaria.org/conferences2017/filesICIW17/KGCC.pdf>.

CONTACT

------------------------------------------

Sarasi Lalithsena, Kno.e.sis Center, Wright State University, USA
sarasi@knoesis.org

Tommaso Soru, AKSW, University of Leipzig, Germany
tsoru@informatik.uni-leipzig.de
Received on Wednesday, 5 April 2017 18:42:20 UTC

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