2022
DOI: 10.1145/3472956
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GraphHINGE: Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network

Abstract: Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations. Recent attempts either rely on explicit path reachability to leverage path-based semantic relatedness or graph neighborhood to learn heterogeneous network representations before predictions. These weakly coupled manners overlook the rich interactions among neighbor nodes, which introduces an early summarization issue. In this article, we propose GraphHINGE ( … Show more

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Cited by 2 publications
(1 citation statement)
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“…There are many research results on dynamic load balancing, non-linear planning and collaborative filtering algorithms abroad. The research on distributed network information mode started late in China [5][6]. For renewable energy power generation system, a multi-stage coordinated control system model composed of solar energy, wind energy, biomass energy is established.…”
Section: Introductionmentioning
confidence: 99%
“…There are many research results on dynamic load balancing, non-linear planning and collaborative filtering algorithms abroad. The research on distributed network information mode started late in China [5][6]. For renewable energy power generation system, a multi-stage coordinated control system model composed of solar energy, wind energy, biomass energy is established.…”
Section: Introductionmentioning
confidence: 99%