A Review of Relational Machine Learning for Knowledge Graphs
Relational machine learning studies methods for the statistical analysis of relational, or graph-structured, data. In this paper, we provide a review of how such statistical models can be “trained” on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to...
| Main Authors: | , , , |
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| Format: | Technical Report |
| Language: | en_US |
| Published: |
Center for Brains, Minds and Machines (CBMM), arXiv
2015
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/100193 |