About: Node Conductance: A Scalable Node Centrality Measure on Big Networks

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Node Conductance: A Scalable Node Centrality Measure on Big Networks
Creator	Zhang, Yan Sun, Fei Lyu, Tianshu
Source	PMC
abstract	Node centralities such as Degree and Betweenness help detecting influential nodes from local or global view. Existing global centrality measures suffer from the high computational complexity and unrealistic assumptions, limiting their applications on real-world applications. In this paper, we propose a new centrality measure, Node Conductance, to effectively detect spanning structural hole nodes and predict the formation of new edges. Node Conductance is the sum of the probability that node i is revisited at r-th step, where r is an integer between 1 and infinity. Moreover, with the help of node embedding techniques, Node Conductance is able to be approximately calculated on big networks effectively and efficiently. Thorough experiments present the differences between existing centralities and Node Conductance, its outstanding ability of detecting influential nodes on both static and dynamic network, and its superior efficiency compared with other global centralities. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-47436-2_40) contains supplementary material, which is available to authorized users.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1007/978-3-030-47436-2_40
has license	no-cc
sha1sum (hex)	8ababc985b108560608764b52f17512e2aae6a47
schema:url	https://doi.org/10.1007/978-3-030-47436-2_40
resource representing a document's title	Node Conductance: A Scalable Node Centrality Measure on Big Networks
has PubMed Central identifier	PMC7206264
schema:publication	Advances in Knowledge Discovery and Data Mining
resource representing a document's body	covid:8ababc985b108560608764b52f17512e2aae6a47#body_text
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