Welcome to Network Science Research Group @ IIIT Kottayam

The Network Science Research Group explores the theory of Complex Networks and is currently focused on understanding how the structure and dynamics of large networks contribute to their robustness. Other interests include the network representation learning, dynamics of Online Social Networks, Functional Brain Networks, and Bibliographic networks.

Research Publications

  1. J M. John; M. Bellingeri; D S. Lekha; D. Cassi; R. Alfieri: Effect of Weight Thresholding on the Robustness of Real-World Complex Networks to Central Node Attacks, Mathematics 2023, 11(16), 3482; DOI: 10.3390/math11163482
  2. Divya P B, D S Lekha, T P Johnson, K Balakrishnan: Vulnerability of link-weighted complex networks in central attacks and fallback strategy, Physica A: Statistical Mechanics and its Applications, Volume 590, 15 March 2022, 126667, DOI: 10.1016/j.physa.2021.126667
  3. D S. Lekha, K. Balakrishnan: Central attacks in complex networks: A revisit with new fallback strategy, Physica A: Statistical Mechanics and its Applications, Volume 549, 1 July 2020, 124347, DOI: 10.1016/j.physa.2020.124347.
  4. K. Balakrishnan, M. Changat, A M. Hinz, D S. Lekha: The Median of Sierpiński Graphs, Discrete Applied Mathematics (Elsevier), Volume 319, Pages 159 - 17015 October 2022, DOI: 10.1016/j.dam.2021.02.005
  5. D S. Lekha, K. Balakrishnan: Central attacks in complex networks: A revisit with new fallback strategy, Physica A: Statistical Mechanics and its Applications, Volume 549, Pages 124347, DOI: 10.1016/j.physa.2020.124347.
  6. K. Balakrishnan, D. S. Lekha, Sunil Kumar R.: Analysis of Co-authorship Network Based on Some Betweenness Centrality Concepts. Inderscience International Journal of Data Science 4 (2), 162-179, DOI: 10.1504/IJDS.2019.100322.
  7. M. Changat, D. S. Lekha, S. Mohandas, H. M. Mulder, A. R. Subhamathi: Axiomatic characterization of the median and antimedian function on a complete graph minus a matching. Discrete Applied Mathematics DOI: 10.1016/j.dam.2016.04.013.
  8. M. Changat, D. S. Lekha, A. R. Subhamathi: Algorithms for the remoteness function, and the median and antimedian sets in l1-graphs. International J. of Computing Science and Mathematics 11/2015; 6(5):480-491, DOI:10.1504/IJCSM.2015.072962.
  9. M. Changat, D. S. Lekha, I. Peterin, A. R. Subhamathi, S. Špacapan: The median game. Discrete Optimization 08/2015; 17, DOI: 10.1016/j.disopt.2015.05.002.
  10. M. Changat, D. S. Lekha, H. M. Mulder, A. R. Subhamathi: Axiomatic Characterization of the Median and Antimedian Functions on Cocktail-Party Graphs and Complete Graphs. In: Ganguly S., Krishnamurti R. (eds) Algorithms and Discrete Applied Mathematics. CALDAM 2015. LNCS, vol 8959. Springer, Cham., DOI: 10.1007/ 978-3-319-14974-5_14.
  11. E. D. Raj, G. Manogaran, G. Srivastava, Y. Wu: Information granulation-based community detection for social networks. IEEE Transactions on Computational Social Systems 8 (1), 122-133
  12. E. D. Raj, L. D. D. Babu: A firefly inspired game dissemination and QoS-based priority pricing strategy for online social network games. International Journal of Bio-Inspired Computation 11 (3), 202-217
  13. E. D. Raj, L. D. D. Babu: Flocking based Evolutionary Computation Strategy for measuring Centrality of Online Social Networks. Applied Soft Computing 58, 495-516
  14. E. D. Raj, L. D. D. Babu: An enhanced trust prediction strategy for online social networks using probabilistic reputation features. Neurocomputing 219, 412-421
  15. E. D. Raj, L. D. D. Babu: A survey on topological properties, network models and analytical measures in detecting influential nodes in online social networks. International Journal of Web Based Communities 13 (1), 137-156
  16. E. D. Raj, L. D. D. Babu: A fuzzy adaptive resonance theory inspired overlapping community detection method for online social networks. Knowledge-Based Systems 113, 75-87
  17. E. D. Raj, L. D. D. Babu: Effective Detection of Modular and Granular Overlaps in Online Social Networks Using Fuzzy ART. International Journal of Fuzzy Systems, 1-16
  18. E. D. Raj, L. D. D. Babu, E. Ariwa: A fuzzy approach to centrality and prestige in online social networks. ICIA-16: Proceedings of the International Conference on Informatics and Analytics, August 2016 Article No.: 61, DOI: 10.1145/2980258.2980395
  19. E. D. Raj, L. D. D. Babu: A model fuzzy inference system for online social network analysis. 2015 International Conference on Computing and Network Communications (CoCoNet), 582-588, IEEE
  20. E. D. Raj, L. D. D. Babu: A Firefly swarm approach for establishing new connections in social networks based on Big Data Analytics. International Journal of Communication Networks and Distributed Systems, Inderscience Publishers, 2015
  21. Joseph, C. T., Chandrasekaran, K.: IntMA: Dynamic Interaction-Aware Resource Allocation for Containerized Microservices, Elsevier Journal of Systems Architecture, 111(101785), 2020, DOI: https://doi.org/10.1016/j.sysarc.2020.101785
  22. J Babu, LS Chandran, M Francis, V Prabhakaran, D Rajendraprasad, NJ Warrier: On graphs with minimal eternal vertex cover number, Conference on Algorithms and Discrete Applied Mathematics, 2019
  23. J Babu, LS Chandran, M Francis, V Prabhakaran, D Rajendraprasad, NJ Warrier: On graphs whose eternal vertex cover number and vertex cover number coincide, Discrete Applied Mathematics 319, 171-182 5, 2022
  24. SM Salam, NJ Warrier, D Chacko, KM Krishnan, KS Sudeep: On chordal and perfect plane near-triangulations, Discrete Applied Mathematics 319, 53-60, 2022
  25. SM Salam, NJ Warrier, D Chacko, KM Krishnan, KS Sudeep: On Chordal and Perfect Plane Triangulations, Conference on Algorithms and Discrete Applied Mathematics, 2019
  26. NJ Warrier, D Chacko, KM Krishnan: Clustering the biological networks using shortest path, Procedia Computer Science 171, 755-760
  27. J Babu, K. M Krishnan, V Prabhakaran and N J. Warrier: Computing eternal vertex cover number of maximal outerplanar graphs in linear time, 23rd Italian Conference of Theoretical Computer Science, 2022
  28. K Nath, S Roy, S Nandi “InOvIn: A fuzzy-rough approach for detecting overlapping communities with intrinsic structures in evolving networks” Applied Soft Computing 89, 106096.
  29. K Nath, S Roy “Detecting intrinsic communities in evolving networks” Social Network Analysis and Mining 9 (1), 1-15.
  30. K Nath, R Dhanalakshmietal “Uncovering hidden community structures in evolving networks based on neighborhood similarity” Journal of Intelligent & Fuzzy Systems 39 (6), 8315-8324.
  31. K Nath, R Shanmugametal “ma-CODE: A multi-phase approach on community detection in evolving networks” Information Sciences 569, 326-343.
  32. K Nath, S Roy, S Nandi “Incremental approach for detecting arbitrary and embedded cluster structures” International Conference on Model and Data Engineering, 220-233.
  33. RA Dkhar, K Nath, S Roy et. al “Evaluating the effectiveness of soft k-means in detecting overlapping clusters” Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies.
  34. K Nath, S Roy, S Nandi “An incremental approach for hierarchical community mining in evolving social graphs” International Journal of Intelligent Enterprise 8 (2-3), 123-141
  35. K Nath, S Roy “A parallel approach to detect communities in evolving networks”International Conference on Big Data Analytics, 188-203
  36. K Nath “Local intrinsic density based community detection using branch-and-bound and Minimum Spanning Tree” Systems and Soft Computing, 200044.
  37. K Nath, S Roy “Overlapping Community Detection in Static and Dynamic Networks: A Qualitative Assessment” Proceedings of the International Conference on Computing and Communication Systems.
  38. K Nath, S Roy “An incremental parallel approach for finding communities in evolving network” Journal of Computational and Theoretical Nanoscience 15 (6-7), 2454-2460.
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