On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
Learning probabilistic models of link structure
The Journal of Machine Learning Research
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Information awareness: a prospective technical assessment
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Link mining: a new data mining challenge
ACM SIGKDD Explorations Newsletter
Fast discovery of connection subgraphs
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining approaches for intrusion detection
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
ACM SIGKDD Explorations Newsletter
Privacy-preserving link discovery
Proceedings of the 2008 ACM symposium on Applied computing
Anomaly detection in data represented as graphs
Intelligent Data Analysis
Measuring the effects of preprocessing decisions and network forces in dynamic network analysis
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning approximate MRFs from large transactional data
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Using friendship ties and family circles for link prediction
SNAKDD'08 Proceedings of the Second international conference on Advances in social network mining and analysis
Learning algorithms for link prediction based on chance constraints
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Temporal Link Prediction Using Matrix and Tensor Factorizations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Role-dynamics: fast mining of large dynamic networks
Proceedings of the 21st international conference companion on World Wide Web
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
GRDB: a system for declarative and interactive analysis of noisy information networks
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Efficient Identification of Linchpin Vertices in Dependence Clusters
ACM Transactions on Programming Languages and Systems (TOPLAS)
sonLP: social network link prediction by principal component regression
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
From biological to social networks: Link prediction based on multi-way spectral clustering
Data & Knowledge Engineering
| Hi-index | 0.00 |
In this paper, we describe the challenges inherent to the task of link prediction, and we analyze one reason why many link prediction models perform poorly. Specifically, we demonstrate the effects of the extremely large class skew associated with the link prediction task. We then present an alternate task --- anomalous link discovery (ALD) --- and qualitatively demonstrate the effectiveness of simple link prediction models for the ALD task. We show that even the simplistic structural models that perform poorly on link prediction can perform quite well at the ALD task.