The 6th International Conference on Analysis of Images, Social Networks, and Texts


Please see the current schedule, speakers, news and registration links at our new site

Please note that all participants should register and pay the conference fee. Please select the appropriate ticket type at our Timepad page. Thanks to our kind sponsors support, we can offer limited number of fee waivers for any category participant. Please contact the organizing committee through the site contact form or email (org - at -

All updates about the conference are published on the Conference Blog, as well as on our Facebook and VK groups.

You are welcome to contact us at any time for assistance.


AIST is a scientific conference on Analysis of Images, Social Networks, and Texts. The conference is intended for computer scientists and practitioners whose research interests involve Internet mathematics and other related fields of data science. Similar to the previous year, the conference will be focused on applications of data mining and machine learning techniques to various problem domains: image processing, analysis of social networks, and natural language processing. We hope that the participants will benefit from the interdisciplinary nature of the conference and exchange experience.

Publication of revised selected papers is performed as a post-proceedings in the Springer's Lecture Notes in Computer Science (LNCS) series.



If you did not participate before in the AIST conference you can take a look at the proceedings of the last three years to get an idea about which kind of papers are accepted and which kinds of topics are discussed at the conference:

Note that the proceedings of this year are published in the LNCS series, not the CCIS series as before.

Download full proceedings of the previous year from Springer (AIST 2016)


The scope of the conference includes but not limited to the following topics: 

  • Social Network Analysis
  • Natural Language Processing
  • Recommender systems and collaborative technologies
  • Process mining
  • Analytics for geoinformation systems
  • Analysis of images and video
  • Discovering and analyzing processes using event data
  • Game analytics
  • Core Data Mining and Machine Learning techniques
  • Semantic Web and Ontologies
  • Educational Data Mining
  • ML & DM for Economics and Social Sciences

This year, we also have a separate track on analysis of dynamic behavior through event data. An analysis of big data, containing dynamic processes of systems’ executions and collaborations in a form of event logs, is a challenging research direction also known as process mining or business process intelligence. Techniques for constructing process models from event logs, finding log and model deviations, and enhancing pre-existing process models with additional information extracted from logs can significantly assist in understanding systems’ behavior. Papers presenting original process mining approaches as well as case studies in discovering and analyzing processes using event data are sought. The scope of the section includes but not limited to the following topics:

  • Algorithms and approaches for the discovery of process models from event logs;
  • Techniques for the discovery of social nets from communication logs;
  • Representation and visualization of models discovered from event logs;
  • Methods for finding deviations between real and expected system’s behavior;
  • Complex event processing to assist process intelligence;
  • Compliance management and conformance checking;
  • Applying process mining techniques in various domains, such as e-government, healthcare, banking, manufacturing, booking systems and others.


The 6th conference on Analysis of Images, Social Networks, and Texts will take place in Moscow, Russia from Thursday, 27th through Saturday, 29th of July 2017.


  • Submission of abstracts (extended): April 30, 2017 May 7, 2017
  • Deadline for papers (extended): May 7, 2017 May 14, 2017 May 17, 2017
  • Notification of Acceptance (extended): June 7, 2017 June 14, 2017 June 19, 2017
  • The Conference: July 27 - 29, 2017



Track 1. General topics of data analysis
Sergey Kuznetsov (Higher School of Economics, Russia)
Amedeo Napoli (LORIA, France)

Track 2. Natural language processing
Natalia Loukachevitch (Moscow State Lomonosov University, Russia)
Alexander Panchenko (University of Hamburg, Germany)

Track 3. Social network analysis
Stanley Wasserman (Indiana University, USA)

Track 4. Analysis of images and video
Victor Lempitsky (Skolkovo Institute of Science and Technology, Russia)
Andrey Savchenko (Higher School of Economics, Russia)

Track 5. Optimization problems on graphs and network structures
Panos M. Pardalos (University of Florida, USA)
Mikhail Khachay (IMM UB RAS & Ural Federal University, Russia)

Track 6. Analysis of dynamic behavior through event data
Wil van der Aalst (Eindhoven University of Technology, The Netherlands)
Irina Lomazova (Higher School of Economics, Russia)


  • Rostislav Yavorskiy, chair (Higher School of Economics, Russia)
  • Aleksey Buzmakov (Higher School of Economics, Russia)
  • Marina Danshina (Moscow Polytechnic University, Russia)
  • Alexander Panchenko (University of Hamburg, Germany)
  • Anna Kalenkova (Higher School of Economics, Russia)


Dmitry Ignatov (Higher School of Economics, Russia)
Mikhail Khachay (IMM UB RAS & Ural Federal University, Russia)
Alexander Panchenko (University of Hamburg, Germany)
Rostislav Yavorskiy (Higher School of Economics, Russia)