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
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Vertex collocation profiles: subgraph counting for link analysis and prediction
Proceedings of the 21st international conference on World Wide Web
Link prediction in complex networks based on cluster information
SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
Link prediction with social vector clocks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Analyzing future communities in growing citation networks
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
| Hi-index | 0.00 |
LPmade is a complete cross-platform software solution for multi-core link prediction and related tasks and analysis. Its first principal contribution is a scalable network library supporting high-performance implementations of the most commonly employed unsupervised link prediction methods. Link prediction in longitudinal data requires a sophisticated and disciplined procedure for correct results and fair evaluation, so the second principle contribution of LPmade is a sophisticated GNU make architecture that completely automates link prediction, prediction evaluation, and network analysis. Finally, LPmade streamlines and automates the procedure for creating multivariate supervised link prediction models with a version of WEKA modified to operate effectively on extremely large data sets. With mere minutes of manual work, one may start with a raw stream of records representing a network and progress through hundreds of steps to generate plots, gigabytes or terabytes of output, and actionable or publishable results.