Zobrazeno 1 - 10
of 25
pro vyhledávání: '"V. S. Subrahmanian"'
Publikováno v:
2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech).
Publikováno v:
ICDM
When a new vulnerability is discovered, a Common Vulnerability and Exposure (CVE) number is publicly assigned to it. The vulnerability is then analyzed by the US National Institute of Standards and Technology (NIST) whose Common Vulnerability Scoring
Autor:
V. S. Subrahmanian
Publikováno v:
IPDPS Workshops
Malicious actors are omnipresent in online social and crowdsourced platforms – vandals on Wikipedia, bots on Twitter, and trolls on various platforms all play a major role in degrading the quality of open information and free discussion on the web.
Autor:
V. S. Subrahmanian, Vadim Kagan
Publikováno v:
SocialSens@IoTDI
Understanding and anticipating the evolution of activity on social media requires insight into social network dynamics and diffusion mechanisms. M3I (Multi-stage, Multimodal, Machine Intelligence) is a platform for modeling online social phenomena th
Publikováno v:
ICDM
Weighted signed networks (WSNs) are networks in which edges are labeled with positive and negative weights. WSNs can capture like/dislike, trust/distrust, and other social relationships between people. In this paper, we consider the problem of predic
Publikováno v:
ASONAM
Autor:
Marc A. Smith, V. S. Subrahmanian, Harald Meier, Clara Pizzuti, Srijan Kumar, Francesca Spezzano
Publikováno v:
ASONAM
Community detection is a hot topic in social networks. The presentation of a different computational paradigm with respect to traditional approaches can be beneficial for researchers to explore new approaches and principles to deal with this problem.
Publikováno v:
ISI
The best known analyses to date of nuclear proliferation networks are qualitative analyses of networks consisting of just hundreds of nodes and edges. We propose SPINN — a computational framework that performs the following tasks. Starting from exi
Publikováno v:
JISIC
We develop a novel approach to predict certain type of stability events (battles, battles won by a government, riots/protests, violence against civilians) in countries by monitoring the content of a mix of traditional news, blog, and social media dat
Publikováno v:
SocialCom
Classical centrality measures like betweenness, closeness, eigenvector, and degree centrality are application and user independent. They are also independent of graph semantics. However, in many applications, users have a clear idea of who they consi