Meta-graph based recommendation fusion over heterogeneous information networks
Heterogeneous Information Network (HIN) is a natural and general representation of data in
modern large commercial recommender systems which involve heterogeneous types of …
modern large commercial recommender systems which involve heterogeneous types of …
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Graphs are structured data that models complex relations between real-world entities.
Heterophilic graphs, where linked nodes are prone to be with different labels or dissimilar …
Heterophilic graphs, where linked nodes are prone to be with different labels or dissimilar …
Leveraging meta-path contexts for classification in heterogeneous information networks
A heterogeneous information network (HIN) has as vertices objects of different types and as
edges the relations between objects, which are also of various types. We study the problem …
edges the relations between objects, which are also of various types. We study the problem …
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 …
Spectral clustering in heterogeneous information networks
A heterogeneous information network (HIN) is one whose objects are of different types and
links between objects could model different object relations. We study how spectral …
links between objects could model different object relations. We study how spectral …
Heterogeneous neural attentive factorization machine for rating prediction
Heterogeneous Information Network (HIN) has been employed in recommender system to
represent heterogeneous types of data, and meta path has been proposed to capture …
represent heterogeneous types of data, and meta path has been proposed to capture …
Social media for opioid addiction epidemiology: Automatic detection of opioid addicts from twitter and case studies
Opioid (eg, heroin and morphine) addiction has become one of the largest and deadliest
epidemics in the United States. To combat such deadly epidemic, there is an urgent need for …
epidemics in the United States. To combat such deadly epidemic, there is an urgent need for …
Meta-graph based hin spectral embedding: Methods, analyses, and insights
Heterogeneous information network (HIN) has drawn significant research attention recently,
due to its power of modeling multi-typed multi-relational data and facilitating various …
due to its power of modeling multi-typed multi-relational data and facilitating various …
Collective classification of spam campaigners on Twitter: A hierarchical meta-path based approach
Cybercriminals have leveraged the popularity of a large user base available on Online
Social Networks~(OSNs) to spread spam campaigns by propagating phishing URLs …
Social Networks~(OSNs) to spread spam campaigns by propagating phishing URLs …
[PDF][PDF] Automatic Opioid User Detection from Twitter: Transductive Ensemble Built on Different Meta-graph Based Similarities over Heterogeneous Information Network …
Opioid (eg, heroin and morphine) addiction has become one of the largest and deadliest
epidemics in the United States. To combat such deadly epidemic, in this paper, we propose …
epidemics in the United States. To combat such deadly epidemic, in this paper, we propose …