TY - GEN
T1 - An effective algorithm for extracting maximal bipartite cliques
AU - Hriez, Raghda Fawzey
AU - Al-Naymat, Ghazi
AU - Awajan, Arafat
N1 - Publisher Copyright:
© 2021 Association for Computing Machinery.
PY - 2021/4/5
Y1 - 2021/4/5
N2 - The reduction of bipartite clique enumeration problem into a clique enumeration problem is a well-known approach for extracting maximal bipartite cliques. In this approach, the graph inflation is used to transform a bipartite graph to a general graph, then any maximal clique enumeration algorithm can be used. However, between every two vertices (in the same set), the traditional inflation algorithm adds a new edge. Therefore incurring high computation overhead, which is impractical and cannot be scaled up to handle large graphs. This paper proposes a new algorithm for extracting maximal bipartite cliques based on an efficient graph inflation algorithm. The proposed algorithm adds the minimal number of edges that are required to convert all maximal bipartite cliques to maximal cliques. The proposed algorithm has been evaluated, using different real world benchmark graphs, according to the correctness of the algorithm, running time (in the inflation and enumeration steps), and according to the overhead of the inflation algorithm on the size of the generated general graph. The empirical evaluation proves that the proposed algorithm is accurate, efficient, effective, and applicable to real world graphs more than the traditional algorithm.
AB - The reduction of bipartite clique enumeration problem into a clique enumeration problem is a well-known approach for extracting maximal bipartite cliques. In this approach, the graph inflation is used to transform a bipartite graph to a general graph, then any maximal clique enumeration algorithm can be used. However, between every two vertices (in the same set), the traditional inflation algorithm adds a new edge. Therefore incurring high computation overhead, which is impractical and cannot be scaled up to handle large graphs. This paper proposes a new algorithm for extracting maximal bipartite cliques based on an efficient graph inflation algorithm. The proposed algorithm adds the minimal number of edges that are required to convert all maximal bipartite cliques to maximal cliques. The proposed algorithm has been evaluated, using different real world benchmark graphs, according to the correctness of the algorithm, running time (in the inflation and enumeration steps), and according to the overhead of the inflation algorithm on the size of the generated general graph. The empirical evaluation proves that the proposed algorithm is accurate, efficient, effective, and applicable to real world graphs more than the traditional algorithm.
KW - Bi-clique
KW - Bipartite clique
KW - Bipartite core
KW - Bipartite graphs
KW - Maximal bipartite clique enumeration problem
UR - https://www.scopus.com/pages/publications/85107503376
U2 - 10.1145/3460620.3460735
DO - 10.1145/3460620.3460735
M3 - Conference contribution
AN - SCOPUS:85107503376
T3 - ACM International Conference Proceeding Series
SP - 76
EP - 81
BT - Proceedings of the 3rd International Conference on Data Science, E-Learning and Information Systems 2021, DATA 2021
PB - Association for Computing Machinery
T2 - 3rd International Conference on Data Science, E-Learning and Information Systems, DATA 2021
Y2 - 5 April 2021 through 7 April 2021
ER -