LPmade: link prediction made easy 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.

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References in zbMATH (referenced in 3 articles )

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  1. Wang, Peng; Xu, Baowen; Wu, Yurong; Zhou, Xiaoyu: Link prediction in social networks: the state-of-the-art (2015) ioport
  2. Aggarwal, Charu C.; Xie, Yan; Yu, Philip S.: A framework for dynamic link prediction in heterogeneous networks (2014)
  3. Lichtenwalter, Ryan N.; Chawla, Nitesh V.: LPmade: link prediction made easy (2011)