Semi-supervised clustering in attributed heterogeneous information networks
A heterogeneous information network (HIN) is one whose nodes model objects of different
types and whose links model objects' relationships. In many applications, such as social …
types and whose links model objects' relationships. In many applications, such as social …
Robust and discriminative labeling for multi-label active learning based on maximum correntropy criterion
Multi-label learning draws great interests in many real world applications. It is a highly costly
task to assign many labels by the oracle for one instance. Meanwhile, it is also hard to build …
task to assign many labels by the oracle for one instance. Meanwhile, it is also hard to build …
Representation learning using Attention Network and CNN for Heterogeneous networks
N Tong, Y Tang, B Chen, L ** across biomedical contexts using compressive data fusion
Motivation: The rapid growth of diverse biological data allows us to consider interactions
between a variety of objects, such as genes, chemicals, molecular signatures, diseases …
between a variety of objects, such as genes, chemicals, molecular signatures, diseases …
Cross multi-type objects clustering in attributed heterogeneous information network
Real-world networks usually consist of a large number of interacting, multi-typed
components which are usually referred as heterogeneous information networks (HIN). HIN …
components which are usually referred as heterogeneous information networks (HIN). HIN …
SCHAIN-IRAM: An efficient and effective semi-supervised clustering algorithm for attributed heterogeneous information networks
A heterogeneous information network (HIN) is one whose nodes model objects of different
types and whose links model objects' relationships. To enrich its information, objects in an …
types and whose links model objects' relationships. To enrich its information, objects in an …
On transductive classification in heterogeneous information networks
A heterogeneous information network (HIN) is used to model objects of different types and
their relationships. Objects are often associated with properties such as labels. In many …
their relationships. Objects are often associated with properties such as labels. In many …
A services classification method based on heterogeneous information networks and generative adversarial networks
With the rapid development of service computing and software technologies, it is necessary
to correctly and efficiently classify web services to promote their discovery and application …
to correctly and efficiently classify web services to promote their discovery and application …
WMGCN: Weighted meta-graph based graph convolutional networks for representation learning in heterogeneous networks
Network embedding has been an effective tool to analyze heterogeneous networks (HNs) by
representing nodes in a low-dimensional space. Although many recent methods have been …
representing nodes in a low-dimensional space. Although many recent methods have been …