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 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.


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 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
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
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,


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

Received on Friday, 1 December 2017 16:56:26 UTC