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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
15 years 10 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
83
Voted
SOCIALCOM
2010
14 years 7 months ago
Measuring Similarity between Sets of Overlapping Clusters
The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
Mark K. Goldberg, Mykola Hayvanovych, Malik Magdon...
DAC
2010
ACM
15 years 29 days ago
Electronic design automation for social networks
Online social networks are a growing internet phenomenon: they connect millions of individuals through sharing of common interests, political and religious views, careers, etc. So...
Andrew DeOrio, Valeria Bertacco
ICPR
2010
IEEE
15 years 3 months ago
Social Network Approach to Analysis of Soccer Game
Video understanding has been an active area of research, where many articles have been published on how to detect and track objects in videos, and how to analyze their trajectorie...
Kyoung-Jin Park, Alper Yilmaz
AAAI
2012
13 years 1 days ago
A Spin-Glass Model for Semi-Supervised Community Detection
Current modularity-based community detection methods show decreased performance as relational networks become increasingly noisy. These methods also yield a large number of divers...
Eric Eaton, Rachael Mansbach