AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
SDM, pp. 144-152, 2018.
Heterogeneous information networksgraph miningnetwork embeddingrepresentation learning
Heterogeneous information networks (HINs) are ubiquitous in real-world applications. Due to the heterogeneity in HINs, the typed edges may not fully align with each other. In order to capture the semantic subtlety, we propose the concept of aspects with each aspect being a unit representing one underlying semantic facet. Meanwhile, networ...More
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