Abstract
The objective of the diversified top-k clique (DTKC) search problem is to find k maximal cliques that cover the maximum number of vertices in a given graph. This problem is equivalent to the well-known maximum clique problem (MaxClique) when k=1. This paper proves the NP-hardness of the DTKC search problem and presents a local search algorithm, named TOPKLS, based on two novel strategies for the DTKC search problem. The first strategy is called enhanced configuration checking (ECC), which is a new variant of a recent effective strategy called configuration checking (CC), for reducing cycling in the local search and improving the diversity of the DTKC search problem. The second strategy is a heuristic to estimate the quality of each maximal clique. Experiments demonstrate that TOPKLS outperforms the existing algorithms on large sparse graphs from real-world applications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
