Abstract
Aiming at the problem of low accuracy and high computational complexity of the traditional social network community recommendation algorithm, a rapid spanning tree detection algorithm is proposed to independently discriminate social network community with the weak connected edge, in order to improve the accuracy of community recommendation and reduce the complexity of algorithm. Firstly, according to the characteristics of social network community recommendation, the maximum spanning tree algorithm is proposed, which is based on the edge weight distribution node similarity, to realize the effective detection of social network community. Secondly, for the proposed algorithm having the problems of repeated adding and deleting of weakly connected edges and the waste of computing resources, a rapid spanning tree detection algorithm based on the independent discrimination of weakly connected edge is proposed so as to further improve the calculation efficiency of the algorithm. Lastly, the effectiveness of the proposed algorithm is verified by comparing the experimental results in the standard test database.
Sign-in/Register to access full text options 
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.
