Abstract
AbstractGiven a graph and a threshold , the maximum quasi‐clique problem amounts to finding a maximum cardinality subset of the vertices in V such that the edge density of the graph induced in G by is greater than or equal to the threshold. This problem is NP‐hard and has a number of applications in data mining, for example, in social networks or phone call graphs. In this work, we present an exact algorithm to solve this problem, based on a quasi‐hereditary property. We also propose a new upper bound that is used for pruning the search tree. Numerical results show that the new approach is competitive and outperforms the best integer programming approaches in the literature. The new upper bound is consistently tighter than previously existing bounds.
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 callMore From: International Transactions in Operational Research
Disclaimer: 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.
