1st International Conference on Computational Aspects of Network Science (CAoNS)

October 19th, 2020

 October 19th, 2020 - October 21st, 2020 

1st International Conference on Computational Aspects of Network Science (CAoNS)

Event submitted on Thursday, August 13th 2020, approved by Charles Villanueva

1st International Conference on Computational Aspects of Network Science (CAoNS), October 19th, 2020Click to Tweet

24 Days Until The Event
October 19th, 2020 - October 21st, 2020
Greece » 
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 Our Review

A conference dedicated to Network Science! If this is your area of expertise then clearly this physical event taking place in October in Greece would be of interest and we wish the organizers the best of luck with it.

Ένα συνέδριο αφιερωμένο στην Επιστήμη Δικτύου

- Review written by Henry Dalziel on Thursday, August 13th 2020.
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Event Summary

The following description was either submitted by the Conference Organizer on Thursday, August 13th 2020, or created by us.

The International Conference on Computational Aspects of Networks Science (CAoNS) will take place at Thessaloniki, the second largest town in Greece, and will be collocated with the 23rd International Conference on Discovery Science (DS).

CAoNS aims at bringing together researchers and practitioners working on areas related to any kind of network, such as networks of devices, world wide web, social, bibliographic, biological networks, complex systems, and so on. Due to numerous applications, there is a growing interest in such systems from the point of view of modeling, capturing, storing, and management.

This is where IT comes into play, e.g. graph databases, machine learning, algorithmic graph theory, distributed, and parallel processing. CAoNS is an interdisciplinary venue for computer scientists, physicists, mathematicians and social scientists aiming at sharing ideas and experiences on all computational aspects related to Network Science and discussing on the broad domains of:

List of Topics

  • Network Geography
  • Search in Network
  • Graph Databases
  • World Wide Web
  • Network Evolution and Growth
  • Neural Networks
  • Recommendation
  • Advertisement Models
  • Security
  • Evaluation

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