13th International Symposium on Intelligent Distributed Computing
IDC 2019
7-9 October 2019, Saint-Petersburg, Russia

 

Big Data for Intelligent Distributed Information Processing (BDIDIP)

 

 

Topics of interest:

 

  • Big Data for intelligent and distributed knowledge representation and reasoning
  • Big Data for intelligent distributed decision making and recommender systems
  • Intelligent distributed natural language processing for sentiment and emotion analysis
  • Stream reasoning for real-time processing of heterogeneous data streams and large knowledge bases
  • Knowledge graph completion
  • Knowledge graph embeddings for entity linking, recommendation, link prediction and validation
  • Machine/Deep learning models for learning knowledge representations from text
  • Semantic Question Answering from Distributed knowledge sources
  • Machine/Deep learning for ontology learning and learning ontological annotations
  • Big Data for distributed knowledge in multi-agent systems

 


Call for papers:

The aim of this special session is to address the pressing needs of the development of new computational methods for intelligent information processing in the context of the recent Big Data paradigm. Traditional AI was interested for several decades in the development and refinement of knowledge representation and reasoning higlighting several aspects including semantics, correctness, and logical approaches. They culminated with the proposal of methods and technologies for semantic information processing, implemented under the generic umbrella of the Semantic Web and/or more recent Linked Open Data paradigms. On the other hand, we are now facing an explosion of information production by ubiquituous and mupltiply interconnected sources representing humans, software applications and physical artefacts. Currently they are handled using methods based on computational statistics and/or machine learning, usually under the umbrella of Data Science. These methods serve descriptive functions by exploring the characteristics and relationships that exist hidden and/or embedded in the data, as well as predictive functions by exploring the trends and laws of data for predicting future knowledge states. The aim of this session is to seek for contributions in either areas of intelligent and / or semantic distributed information processing, with the aim of progressing and possibly bridging the gap by cross-fertilization between both areas in the context of the recent Big Data paradigm.

 

Submissions and reviews will be handled via EasyChair system: https://easychair.org/conferences/?conf=idc2019

 

 

Important dates:

 

Full paper submission: A̶p̶r̶i̶l̶ ̶9̶t̶h,  ̶A̶p̶r̶i̶l̶ ̶2̶3̶r̶d̶, May 6th 2019 (final extension!)

Notification of acceptance: ̶M̶a̶y̶ ̶3̶1̶s̶t̶, ̶J̶u̶n̶e̶ ̶7̶t̶h̶, June 11, 2019

Final (camera ready) paper submission: ̶J̶u̶n̶e̶ ̶4̶t̶h̶, ̶J̶u̶n̶e̶ ̶1̶7̶t̶h̶, June 19, 2019

Registration for authors: June 20, 2019

Special session date: October 7th/8th/9th, 2019

 

 

Program chairs:

 

 

 

Technical Program Committee (to be confirmed):

 

 

Laboratory of Computer Security Problems

St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)

Saint Petersburg National Research University of Information Technologies, Mechanics and Optics  (ITMO University)

Prof. Igor Kotenko

Russia, 199178, St. Petersburg., No. 39, 14-th Linia, VI

Phone / Fax:   +7-812-328-71-81 / +7-812-328-44-50

E-mail: idc2019@comsec.spb.ru