Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery

ECML/PKDD (2), pp. 37-54, 2018.

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Abstract:

Heterogeneous networks are widely used to model real-world semi-structured data. The key challenge of learning over such networks is the modeling of node similarity under both network structures and contents. To deal with network structures, most existing works assume a given or enumerable set of meta-paths and then leverage them for the ...More

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