Are we friends or enemies? let's ask thy neighbour!

Roshni Chakraborty, Nilotpal Chakraborty

Research output: Contribution to conference without publisher/journalPosterResearch

1 Citation (Scopus)

Abstract

With the richness of interactions among users emerging through different social media applications, drawing conclusive evidence about the sign of these relations (positive and negative) is receiving significant attention. In this paper, we propose an adaptive link prediction system which tactfully ensembles both local and nonlocal attributes of an edge to predict it's sign while considering the high variance of the network and handling the inherent sparsity of the graph. Experimental validation on signed networks, like Slashdot and Epinions indicate the proposed approach can ensure high significant prediction accuracy when compared with the existing research works.

Original languageEnglish
Publication date17 Mar 2020
Number of pages2
DOIs
Publication statusPublished - 17 Mar 2020
Event25th International Conference on Intelligent User Interfaces, IUI 2020 - Cagliari, Italy
Duration: 17 Mar 202020 Mar 2020

Conference

Conference25th International Conference on Intelligent User Interfaces, IUI 2020
Country/TerritoryItaly
CityCagliari
Period17/03/202020/03/2020
SponsorACM Special Interest Group on Artificial Intelligence (SIGAI), Specialist Interest Group in Computer-Human Interaction of the ACM (SIGCHI)

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