Processing Big Graphs

Project Description: The huge amount of data to be represented using very large graphs often exceeds the memory resources of conventional computers. Links between data elements (or edges) can take up a considerable amount of memory. In this project we aim at devising effective techniques for efficient storage and retrieval of data represented by big graphs, such as social networks.

PI: Faisal N. Abu-Khzam

Publications:

F. N. Abu-Khzam and R. H. Mouawi. Concise Fuzzy Representation of Big Graphs: a Dimensionality Reduction Approach. CoRR abs/1803.03114 (2018)

F. N. Abu-Khzam, A. Haj Ahmad and R. H. Mouawi. Concise Fuzzy Representation of Big Graphs: a Dimensionality Reduction Approach, in Proceedings of the Data Compression Conference (DCC 2020): 356.

Previous publications (from related older projects):

G. L. Rogers, A. D. Perkins, C. A. Phillips, J. D. Eblen, F. N. Abu-Khzam and M. A. Langston. Using out-of-core techniques to produce exact solutions to the maximum clique problem on extremely large graphs. in Proceedings, ACS/IEEE International Conference on Computer Systems and Application (AICCSA 2009): pages 374-381, 2009.