jmlr jmlr2011 jmlr2011-50 jmlr2011-50-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Ryan N. Lichtenwalter, Nitesh V. Chawla
Abstract: 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 highperformance 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. Keywords: link prediction, network analysis, multicore, GNU make, PropFlow, HPLP
David Liben-Nowell and Jon Kleinberg. The link-prediction problem for social networks. Journal of the American Society for Inf. Science and Tech., 58(7):1019–1031, 2007. Ryan N. Lichtenwalter, Jake T. Lussier, and Nitesh V. Chawla. New perspectives and methods in link prediction. In Proc. of the 16th ACM SIGKDD Intl. Conf. on Knowledge Disc. and Data Mining, pages 243–252, 2010. Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco, California, USA, second edition, 2005. 2492