CFP - Int. Workshop on Semantics in the Deep: Semantic Analytics for Big Data (SEDSEAL 2018)

(apologies for cross-postings)

*                           International Workshop on                      *
*          Semantics in the Deep: Semantic Analytics for Big Data          *
*                              (SEDSEAL 2018)                              *
*                                                                          *
*                  URL:                *
*                                                                          *
*                                                                          *
*                         in conjunction with the                          *
*                                                                          *
*                     14th International Conference on                     *
*           Artificial Intelligence Applications and Innovations           *
*                                (AIAI 2018)                               *
*                                                                          *
*                     May 25-27, 2018, Rhodes, Greece                      *
*                                                                          *

                              CALL FOR PAPERS


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
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
results. To this end, machine- and deep-learning techniques, while being
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
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


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,
- 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


Papers reporting original and unpublished research results on the above and
related topics are solicited. Authors should submit a paper with up to 10
(in English) in single-column Springer format following the Springer IFIP
format guidelines. Submissions must be in electronic form as PDF files
and should be uploaded at
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
will be considered for publication in international journals.


Paper submission: 3/2/2018
Author notification: 28/2/2018
Camera-ready submission: 9/3/2018
Workshop Dates: 25-27/5/2018


Dr. Dimitrios A. Koutsomitropoulos, University of Patras, Greece
Prof. Spiridon D. Likothanassis, University of Patras, Greece


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


For additional information, please contact:
Dr. Dimitrios A. Koutsomitropoulos,
Prof. Spiridon D. Likothanassis,

Received on Friday, 1 December 2017 16:51:03 UTC