Representation learning on heterogenous information networks
In real world, most of the information networks are heterogeneous in nature, which contains different types of nodes and relationships. Representation learning or feature learning techniques are needed to extract features of these Heterogeneous Information Networks (HIN) and convert them to low dime...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/150188 |