| Document Date: 2011-11-19 02:38:52
Open Document File Size: 154,66 KBShare Result on Facebook
Company ACM Press / Google / Microsoft / / Country United States / / / Facility Computer Science Carnegie Mellon University / Carnegie Mellon University / / IndustryTerm different products / recommendation network / effort mining topics / chemical compound / proposed approximate graph isomorphism algorithm / per-group recommendation networks / large social networks / substructure pattern mining / efficient algorithm / Web-crawling / free e-mail services / search space using node / per-product recommendation networks / product recommendation network / mass media / frequent subgraph mining / video network / large on-line retailer / direct advertising / book network / approximate solution / large-scale on-line data / technology domain / music product / polynomial-time algorithm / real recommendation network / heuristic solution / power law / social networks / large person-to-person recommendation network / social network / approximate solutions / music network / random networks / efficient algorithms / / Organization G8 / G20 / National Science Foundation / G7 / Pennsylvania Infrastructure Technology Alliance / Carnegie Mellon University / Cornell University / / Position author / simple model of global cascades on random networks / simple model of global cascades / / Product CCR / / PublishedMedium Free Press / American Journal of Sociology / / Technology efficient algorithm / proposed approximate graph isomorphism algorithm / bioinformatics / efficient algorithms / apriori-based algorithm / polynomial-time algorithm / viral marketing / /
SocialTag |
Patterns of Influence in a Recommendation Network Jure Leskovec1, Ajit Singh1 , and Jon Kleinberg2 1 2