Determining influence in a network

An influence maximization process efficiently identifies an influential set of nodes with which to seed a diffusion process using the transposition of a graph representing the network. This approach offers an acceptable tradeoff between runtime complexity and accurate approximation. In addition, usi...

Full description

Saved in:
Bibliographic Details
Main Authors BRAUTBAR MICHAEL AVRAHAM, BORGS CHRISTIAN HERWARTH, CHAYES JENNIFER TOUR, LUCIER BRENDAN JAMES
Format Patent
LanguageEnglish
Published 14.06.2016
Subjects
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online AccessGet full text

Cover

More Information
Summary:An influence maximization process efficiently identifies an influential set of nodes with which to seed a diffusion process using the transposition of a graph representing the network. This approach offers an acceptable tradeoff between runtime complexity and accurate approximation. In addition, using an approximation condition, the influence maximization process may be further tuned to dramatically reduce the computational complexity even more in certain circumstances while allowing a fallback to the unturned influence maximization process if the approximation condition is not satisfied.
Bibliography:Application Number: US201213629978