CMU report: On the Beaten Path: Exploitation of Entities Interactions For Predicting Potential Link

Y. Seo and K. Sycara
tech. report CMU-RI-TR-06-36, Robotics Institute, Carnegie Mellon University, August, 2006.

Abstract: We propose a new non-parametric link analysis algorithm that predicts a potential link between entities given a set of different relational patterns. The proposed method first represents different types of relations among entities by constructing the corresponding number of factorized matrices from the original entity-by-relation matrices. The prediction of a possible link between entities is done by linearly summing the weighted distances in the latent spaces. A logistic regression is used to estimate regression coefficients of distances in the latent spaces. From the experimental comparisons with various algorithms, our algorithm performs best in precision and second-best in recall measure. (pdf)