- From: Dimitrios Koutsomitropoulos <kotsomit@ceid.upatras.gr>
- Date: Fri, 12 Jan 2018 19:31:48 +0200
- To: "Dimitrios Koutsomitropoulos" <kotsomit@ceid.upatras.gr>
(apologies for cross-postings)
############################################################################
*NEW: JOURNAL SPECIAL ISSUE*
SEDSEAL papers to appear in a special issue of the Data int. journal
(http://www.mdpi.com/journal/data)
############################################################################
============================================================================
* International Workshop on *
* Semantics in the Deep: Semantic Analytics for Big Data *
* (SEDSEAL 2018) *
* *
* URL: https://sedseal2018.ceid.upatras.gr *
* *
* *
* in conjunction with the *
* *
* 14th International Conference on *
* Artificial Intelligence Applications and Innovations *
* (AIAI 2018) *
* *
* May 25-27, 2018, Rhodes, Greece *
* *
============================================================================
****************************************************************************
CALL FOR PAPERS
****************************************************************************
==============
AIMS AND SCOPE
==============
Recent advances in availability of information on the Internet, storage
space
and web generated content have paved the way for the advent of Big Data. The
well-known 4 Vs (Velocity, Variety, Volume, Value) that characterize Big
Data
can find a match in intelligent ways for management, manipulation and value-
extraction. It is widely acknowledged that the recent surge in AI and
especially
machine learning is exactly due to these advancements. The Semantic Web can
offer a well-studied, although ever advancing, toolbox that can address Big
Data
requirements and contribute towards their meaningful analysis. Still, there
are
often issues that need to be tackled with like bootstrapping, efficiency and
standardized business processes for semantic analytics to achieve
satisfactory
results. To this end, machine- and deep-learning techniques, while being
shunned
in the past, have been shown to have considerable contributions towards Big
Data
analytics and to overcome Semantic Web inherent limitations.
Therefore, the aim of this workshop is to bring together researchers and
practitioners to look deeper into how Semantic Web technologies can
contribute
towards Big Data analytics. This can be achieved either by extracting value
out
of these data (through reasoning), creating sustainable ontology models,
offering a solid foundation for deploying learning techniques or anything in
between.
==================
TOPICS OF INTEREST
==================
Indicative topics of interest for the workshop include, but are not limited
to:
- Ontologies for big data
- Semantic applications in big data domains including open datasets, linked
data, scholarly information, e-learning, economics, insurance, sensors,
bioinformatics
- Reasoning approaches for knowledge extraction
- Ontology learning
- Topic modeling
- Linked Data
- NLP and word embedding
- Semantic deep learning
- Semantic lakes
- OBDA approaches for big data access
- Evaluation techniques
- Ontologies as training sets
- Ontology evolution and learning feedback
- Scalability issues
================
PAPER SUBMISSION
================
Papers reporting original and unpublished research results on the above and
related topics are solicited. Authors should submit a paper with up to 10
pages
(in English) in single-column Springer format following the Springer IFIP
AICT
format guidelines. Submissions must be in electronic form as PDF files
and should be uploaded at
https://easychair.org/conferences/?conf=sedseal2018.
Submitted papers will be peer-reviewed by at least 2 independent members of
the
program committee.
At least one author of each accepted paper must be registered and present
the
paper at the workshop. All accepted papers will be included in the
conference
proceedings and published in the Springer IFIP AICT (Advances in Information
and
Communication Technology series).
Extended versions of selected workshop papers will be considered for
publication
in a special issue of the Data int. journal
(http://www.mdpi.com/journal/data,
open-access, no charge), in addition to the main conference journals
(http://easyconferences.eu/aiai2018/spissue.html).
===============
IMPORTANT DATES
===============
Paper submission: 3/2/2018
Author notification: 28/2/2018
Camera-ready submission: 9/3/2018
Workshop Dates: 25-27/5/2018
============
ORGANIZATION
============
Dr. Dimitrios A. Koutsomitropoulos, University of Patras, Greece
Prof. Spiridon D. Likothanassis, University of Patras, Greece
============================
PROGRAM COMMITEE (tentative)
============================
Andreas Andreou, Cyprus University of Technology, Cyprus
Christos Alexakos, University of Patras, Greece
Dimitrios Koutsomitropoulos, University of Patras, Greece
Dimitrios Tsolis, University of Patras, Greece
Dimitrios Tzovaras, CERTH/ITI, Greece
Efstratios Georgopoulos, Technological Institute of Kalamata, Greece
Filipe Portela, University of Minho, Spain
Jouni Tuominen, University of Helsinki, Finland
Konstantinos Votis, CERTH/ITI, Greece
Miguel-Angel Sicilia, University of Alcala, Spain
Minjuan Wang, San Diego State University, US
Spiridon Likothanassis, University of Patras, Greece
Vassilis Plagianakos, University of Thessaly, Greece
=======
CONTACT
=======
For additional information, please contact:
Dr. Dimitrios A. Koutsomitropoulos, kotsomit@ceid.upatras.gr
Prof. Spiridon D. Likothanassis, likothan@ceid.upatras.gr
Received on Saturday, 13 January 2018 00:32:29 UTC