C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Robust Classification for Imprecise Environments
Machine Learning
Machine Learning
The case for anomalous link discovery
ACM SIGKDD Explorations Newsletter
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Local Probabilistic Models for Link Prediction
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
It's who you know: graph mining using recursive structural features
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Diversified ranking on large graphs: an optimization viewpoint
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting place features in link prediction on location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Time aware index for link prediction in social networks
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Link prediction via matrix factorization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Who will follow you back?: reciprocal relationship prediction
Proceedings of the 20th ACM international conference on Information and knowledge management
Link prediction: the power of maximal entropy random walk
Proceedings of the 20th ACM international conference on Information and knowledge management
Structural link analysis and prediction in microblogs
Proceedings of the 20th ACM international conference on Information and knowledge management
LPmade: Link Prediction Made Easy
The Journal of Machine Learning Research
When will it happen?: relationship prediction in heterogeneous information networks
Proceedings of the fifth ACM international conference on Web search and data mining
Inferring social ties across heterogenous networks
Proceedings of the fifth ACM international conference on Web search and data mining
On social computing research collaboration patterns: a social network perspective
Frontiers of Computer Science in China
Vertex collocation profiles: subgraph counting for link analysis and prediction
Proceedings of the 21st international conference on World Wide Web
Event-based social networks: linking the online and offline social worlds
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
RolX: structural role extraction & mining in large graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarization-based mining bipartite graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Cross-domain collaboration recommendation
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Back-buy prediction based on TriFG
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Feature selection for link prediction
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Proceedings of the 21st ACM international conference on Information and knowledge management
Evolution of a location-based online social network: analysis and models
Proceedings of the 2012 ACM conference on Internet measurement conference
Classification-Based prediction on the retweet actions over microblog dataset
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
ALIVE: a multi-relational link prediction environment for the healthcare domain
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
Classification Analysis in Complex Online Social Networks Using Semantic Web Technologies
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Link Prediction: Fair and Effective Evaluation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Enhancing Academic Event Participation with Context-aware and Social Recommendations
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Link Prediction Using BenefitRanks in Weighted Networks
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Learning latent friendship propagation networks with interest awareness for link prediction
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Link prediction with social vector clocks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Organizational overlap on social networks and its applications
Proceedings of the 22nd international conference on World Wide Web
How do people link?: analysis of contact structures in human face-to-face proximity networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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
Link prediction in human mobility networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Learning to predict reciprocity and triadic closure in social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Different approaches to community evolution prediction in blogosphere
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Inferring anchor links across multiple heterogeneous social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Co-occurrence prediction in a large location-based social network
Frontiers of Computer Science: Selected Publications from Chinese Universities
Proximity measures for link prediction based on temporal events
Expert Systems with Applications: An International Journal
Computationally efficient link prediction in a variety of social networks
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Who proposed the relationship?: recovering the hidden directions of undirected social networks
Proceedings of the 23rd international conference on World wide web
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This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse networks presents a significant challenge due to the inherent disproportion of links that can form to links that do form. Previous research has typically approached this as an unsupervised problem. While this is not the first work to explore supervised learning, many factors significant in influencing and guiding classification remain unexplored. In this paper, we consider these factors by first motivating the use of a supervised framework through a careful investigation of issues such as network observational period, generality of existing methods, variance reduction, topological causes and degrees of imbalance, and sampling approaches. We also present an effective flow-based predicting algorithm, offer formal bounds on imbalance in sparse network link prediction, and employ an evaluation method appropriate for the observed imbalance. Our careful consideration of the above issues ultimately leads to a completely general framework that outperforms unsupervised link prediction methods by more than 30% AUC.