Project details for ExtRESCAL

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Version:
0.7.2
Submitter:
nzhiltsov
Author(s):
Nikita Zhiltsov
Posted:
20 January 2015
Last Updated:
20 January 2015
Open Source License:
apache 2.0
Programming Language(s):
python

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Logo ExtRESCAL 0.7.2

by nzhiltsov - January 20, 2015, 00:35:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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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 leverages on the SciPy Sparse module.

Project Page

https://github.com/nzhiltsov/Ext-RESCAL

Features

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

[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.

[3] Nickel, Maximilian. Tensor factorization for relational learning. Diss. München, Ludwig-Maximilians-Universität, Diss., 2013, 2013.

Expected Applications

  • Link Prediction
  • Collaborative Filtering
  • Entity Search

Prerequisites

  • Python 2.7+
  • Numpy 1.6+
  • SciPy 0.12+
Changes to previous version:
  • Improve (speed up) initialization of A by summation
BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Platform Independent
Data Formats: Csv
Tags: Tensor, Factorization
Archive: download here

Other available revisons

Version Changelog Date
0.7.2
  • Improve (speed up) initialization of A by summation
January 20, 2015, 00:35:15
0.7.1
  • Grealy improve the memory consumption for all scripts after refactoring to using csr_matrix
  • Fix the eigenvalue initialization
October 11, 2014, 17:08:01
0.6
  • Make the extended algorigthm output fixed (by replacing random initialization)
  • Add handling of float values in the extended task
  • Add the util for matrix pseudo inversion
  • Switch to Apache License 2.0
March 21, 2014, 16:22:58
0.5.1

Initial Announcement on mloss.org.

July 3, 2013, 09:38:02

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