Call for Book Chapters: Principles of Big Graph- In-depth Insight by NIT Silchar: Submit by Sep 15

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About the Book

Big Graph is one of the most recent emerging research fields which is gaining enormous popularity among academicians, industrialists, and practitioners. Also, Big Graph is applied in many research domains, for instance, Bioinformatics, Social networking, Computer Networking, Complex Networks, Data Streaming and many more.

Big Graph has become an important research field due to ever growing data size. Conventional Graph databases and analytics are unable to solve the dilemma of scalability of graph data. Processing large scale graph data becomes expensive in terms of computation. Therefore, Big Graph plays a vital role in mining meaningful information from graph data. However, Big Graph analytics, mining and storing are also a big deal.

Nowadays, the World is interconnected through the Internet, for instance, social media. Not only social media relies on Big Graph technology but also biological networks, scholar article citation networks, protein protein interaction, and semantic networks rely on Big Graph.

Therefore, Big Graph is able to influence the researchers, developers and practitioners. Since, these graphs consist of millions of nodes and trillion of edges. Hence, processing of these large graphs becomes a grand challenge. The Big Graphs are growing exponentially and it needs a large computing machinery.

Topics
  • Big Data and Big Graph
  • NoSQL for Big Graph
  • Big Graph Architecture
  • Big Graph Mining and Analytics
  • Big Graph Visualization
  • Big Graph Applications
  • In-memory Big Graph
  • In-memory Big Graph Storage Architecture
  • In-memory Big Graph Frameworks
  • In-memory Big Graph databases
  • In-memory Big Graph Analytics
  • Big Graph Databases: SSD and HDD based Big Graph
  • Big Graph frameworks based on SSD
  • SSD-based Big Graph Databases
  • SSD-based Big Graph Analytics
  • Big Graph Framework based on HDD
  • HDD-based Big Graph Databases
  • HDD-based Big Graph Analytics
  • Big Graph Mining: Discoveries and Analytics
  • Big Graph processing frameworks
  • Pregel and Pregelix, GraphLab, Blogel, Pegasus, GraphX, Giraph, Mizan
  • GPS, Graph Sample and Hold
Important dates
  • Submission deadline: September 15, 2020
  • Author notification: November 15, 2020
Editors
  • Dr. Ripon Patgiri, National Institute of Technology Silchar
  • Ganesh Chandra Deka, Deputy Director, International Cooperation & Technology, Ministry of Skill Development and Entrepreneurship, Govt. of India New Delhi, INDIA
  • Dr. Anupam Biswas, National Institute of Technology Silchar
Contact

Email: ripon[at]cse.nits.ac.in, anupam[at]cse.nits.ac.in and ganeshdeka2000[at]gmail.com

Click here for submission & more details.

 

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