- Recurrent knowledge graph embedding for effective recommendation🔍
- Recurrent Knowledge Graph Embedding for Effective ...🔍
- Recurrent knowledge graph embedding for effective ...🔍
- sunzhuntu/Recurrent|Knowledge|Graph|Embedding🔍
- Searching Recurrent Architecture for Knowledge Graph Embedding🔍
- A Multi|model Recurrent Knowledge Graph Embedding for ...🔍
- Paper Session 7🔍
- A Survey on Knowledge Graph Embedding🔍
Recurrent Knowledge Graph Embedding for Effective ...
Recurrent knowledge graph embedding for effective recommendation
This paper presents RKGE, a KG embedding approach that automatically learns semantic representations of both entities and paths between entities.
Recurrent Knowledge Graph Embedding for Effective ...
Recurrent Knowledge Graph Embedding for. Effective Recommendation. Zhu Sun1, Jie Yang2, Jie Zhang1, Alessandro Bozzon3, Long-Kai Huang1, Chi Xu4∗. 1Nanyang ...
Recurrent Knowledge Graph Embedding for Effective ...
Recurrent knowledge graph embedding for effective recommendation. Sun, Zhu; Yang, Jie; Zhang, Jie; Bozzon, Alessandro; Huang, Long Kai; Xu, Chi. DOI. 10.1145 ...
Recurrent knowledge graph embedding for effective recommendation
RKGE is presented, a KG embedding approach that automatically learns semantic representations of both entities and paths between entities for characterizing ...
Recurrent knowledge graph embedding for effective ...
Abstract. Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing methods mainly rely on hand-engineered features from KGs ...
sunzhuntu/Recurrent-Knowledge-Graph-Embedding - GitHub
This is for the knowledge graph embedding recommendation framework – RKGE - sunzhuntu/Recurrent-Knowledge-Graph-Embedding.
Recurrent knowledge graph embedding for effective recommendation
Recurrent knowledge graph embedding for effective recommendation. Sun, Zhu Nanyang Technological University, Singapore; Yang, Jie University of Fribourg ...
Searching Recurrent Architecture for Knowledge Graph Embedding
Authors. Yongqi Zhang, Quanming Yao, Lei Chen. Abstract. Knowledge graph (KG) embedding is well-known in learning representations of KGs.
A Multi-model Recurrent Knowledge Graph Embedding for ...
Request PDF | On Jun 16, 2024, Dionisis Kotzaitsis and others published A Multi-model Recurrent Knowledge Graph Embedding for Contextual Recommendations ...
Paper Session 7: Recurrent knowledge graph embedding for ...
Recurrent knowledge graph embedding for effective recommendation Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, ...
Recurrent knowledge graph embedding for effective ...
Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing methods mainly rely on hand-engineered features from KGs (e.g., ...
A Survey on Knowledge Graph Embedding: Approaches ... - Medium
These translation-based models have been widely used and have shown good performance on various knowledge graph tasks, such as link prediction ...
A Multi-model Recurrent Knowledge Graph Embedding for ... - OUCI
Ehrlinger, L., Wöß, W.: Towards a definition of knowledge graphs. In: Joint Proceedings of the Posters and Demos Track of SEMANTiCS2016 and SuCCESS 2016, ...
Searching Recurrent Architecture for Knowledge Graph Embedding
In this paper, we observe that the relational path is an important and effective data structure that can preserve both short-term and long-term information in ...
Recurrent knowledge graph embedding for effective ...
Recurrent knowledge graph embedding for effective recommendation. Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, Chi Xu. Research output ...
Leveraging Knowledge Graph Embedding for Effective ... - arXiv
[21] also extracted various meta-paths between a user and an item, and then integrated different path through a recurrent neural network and a ...
A review of recommender systems based on knowledge graph ...
recurrent knowledge graph embedding for effective recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems (2018), pp. 297-305.
A Knowledge Graph based Bidirectional Recurrent Neural Network ...
In this paper, we present a model which incorporates biomedical knowledge graph, graph embedding and deep learning methods for literature-based discovery.
CDRGN-SDE: Cross-Dimensional Recurrent Graph Network with ...
... Recurrent Graph Network with neural Stochastic Differential Equation for temporal knowledge graph embedding ... effectively addresses the temporal knowledge ...
Effective knowledge graph embeddings based on multidirectional ...
(2013) explore frequent side-effect profiles on the basis of integrated drug and target descriptors using two machine learning methods: decision trees and ...