Local Structural Aware Heterogeneous Information Network Embedding Based on Relational Self-Attention Graph Neural Network
نویسندگان
چکیده
منابع مشابه
Graph Embedding with Rich Information through Bipartite Heterogeneous Network
Graph embedding has attracted increasing attention due to its critical application in social network analysis. Most existing algorithms for graph embedding only rely on the typology information and fail to use the copious information in nodes as well as edges. As a result, their performance for many tasks may not be satisfactory. In this paper, we proposed a novel and general framework of repre...
متن کاملHINE: Heterogeneous Information Network Embedding
Network embedding has shown its effectiveness in embedding homogeneous networks. Compared with homogeneous networks, heterogeneous information networks (HINs) contain semantic information from multi-typed entities and relations, and are shown to be a more effective model for real world data. The existing network embedding methods fail to explicitly capture the semantics in HINs. In this paper, ...
متن کاملSTRUCTURAL RESPONSE OBSERVER BASED ON ARTIFICIAL NEURAL NETWORK
Structural vibration control is one of the most important features in structural engineering. Real-time information about seismic resultant forces is required for deciding module of intelligent control systems. Evaluation of lateral forces during an earthquake is a complicated problem considering uncertainties of gravity loads amount and distribution and earthquake characteristics. An artificia...
متن کاملHeterogeneous Information Network Embedding for Recommendation
Due to the flexibility in modelling data heterogeneity, heterogeneous information network (HIN) has been adopted to characterize complex and heterogeneous auxiliary data in recommender systems, called HIN based recommendation. It is challenging to develop effective methods for HIN based recommendation in both extraction and exploitation of the information from HINs. Most of HIN based recommenda...
متن کاملHeterogeneous Information Network Embedding for Meta Path based Proximity
A network embedding is a representation of a large graph in a lowdimensional space, where vertices are modeled as vectors. The objective of a good embedding is to preserve the proximity (i.e., similarity) between vertices in the original graph. This way, typical search and mining methods (e.g., similarity search, kNN retrieval, classification, clustering) can be applied in the embedded space wi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: 2169-3536
DOI: 10.1109/access.2021.3090055