NDLI: Evaluate Nodes Importance in the Network Using Data Field Theory

Content Provider	IEEE Xplore Digital Library
Author	He Nan Gan Wen-yan Li De yi
Copyright Year	2007
Description	Author affiliation: Beihang Univ., Beijing (He Nan)
Abstract	Evaluating nodes importance in the network is an important research topic in the fields of complex networks, social network analysis and graph-based data mining. Enlightened by the knowledge of physical field, this paper proposes a topological ranking algorithm based on data field theory. Its basic idea is that each node in the network can be viewed as a material particle which creates a potential field around itself and the interaction of all nodes forms a topological field over the network. By defining and computing the topological potential score of each node, we can obtain a more accurate global ranking which can reflect nodes importance in the network. The theory and experimental results on toy and real-world networks indicate that when each node only influences its neighbors, the topological ranking is consistent with the degree ranking; as the node's influence spreads, the topological ranking turns out to have similar linear relevance with PageRank sort; when the influence reaches the diameter of the network, the topological ranking is close to the closeness ranking this time. Hence, this method not only provides a general framework for some classic ranking measures, but is also able to obtain an accurate ranking of vital nodes by optimizing correlative parameters, which can reveal the position differences of network topology.
Starting Page	1225
Ending Page	1234
File Size	354383
Page Count	10
File Format	PDF
ISBN	0769530389
DOI	10.1109/ICCIT.2007.88
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-21
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Social network services Complex networks Data engineering Systems engineering and theory Computer networks Data mining Helium Information technology Gallium nitride Diseases
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Evaluate Nodes Importance in Directed Network Using Topological Potential

Evaluating Node Importance in Complex Network Based on Enron Database

A New Method for Evaluating Node Importance in Complex Networks Based on Data Field Theory

Trust Relationship Modelling in E-commerce-Based Social Network

Social Behavior Association and Influence in Social Networks

Discovery of Core-Nodes in Event-Based Social Networks

Information Technology Capabilities for Digital Social Networks

Social Graph Generation & Forecasting Using Social Network Mining

Collaborative Mining in Multiple Social Networks Data for Criminal Group Discovery

Evaluate Nodes Importance in the Network Using Data Field Theory

Similar Documents

Evaluate Nodes Importance in Directed Network Using Topological Potential

Evaluating Node Importance in Complex Network Based on Enron Database

A New Method for Evaluating Node Importance in Complex Networks Based on Data Field Theory

Trust Relationship Modelling in E-commerce-Based Social Network

Social Behavior Association and Influence in Social Networks

Discovery of Core-Nodes in Event-Based Social Networks

Information Technology Capabilities for Digital Social Networks

Social Graph Generation & Forecasting Using Social Network Mining

Collaborative Mining in Multiple Social Networks Data for Criminal Group Discovery

Evaluate Nodes Importance in the Network Using Data Field Theory