Description:

Ext-RESCAL is a memory efficient implementation of RESCAL, a state-of-the-art algorithm for DEDICOM-like tensor factorization. Ext-RESCAL is written in Python and relies on the SciPy Sparse module.

• 3-D sparse tensor factorization [1];
• Joint 3-D sparse tensor and 2-D sparse matrix factorization (extended version) [2];
• The implementation provably scales well to the domains with millions of nodes on the affordable hardware;
• Handy input format;

[1] M. Nickel, V. Tresp, H. Kriegel. A Three-way Model for Collective Learning on Multi-relational Data // Proceedings of the 28th International Conference on Machine Learning (ICML'2011). - 2011.

[2] M. Nickel, V. Tresp, H. Kriegel. Factorizing YAGO: Scalable Machine Learning for Linked Data // Proceedings of the 21st international conference on World Wide Web (WWW'2012). - 2012.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Platform Independent

Data Formats: Csv

Tags: Tensor, Factorization

Archive: download here

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