Modelling relational data using Bayesian clustered tensor factorization
We consider the problem of learning probabilistic models for complex relational structures between various types of objects. A model can help us "understand" a dataset of relational facts in at least two ways, by finding interpretable structure in the data, and by supporting predictions, o...
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| Format: | Article |
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Neural Information Processing Systems Foundation
2017
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| Online Access: | http://hdl.handle.net/1721.1/112916 |