Knowledge graphs in the biomedical context are spreading rapidly attracting the strong interest of the research due to their natural way of representing biomedical knowledge by integrating heterogeneous domains (genomic, pharmaceutical, clinical etc.). In this paper we will give an overview of the ...
Mining valuable hidden knowledge from large-scale data relies on the support of reasoning technology. Knowledge graphs, as a new type of knowledge representation, have gained much attention in natural language processing. Knowledge graphs can effectively organize and represent knowledge so that it can ...
概述 Current real-world knowledge graphs are usuallyincompleteand need aninference engineto predict links andcomplete the missing factsamong entities available in the KG. Relation classification or inference from information already available KG is calledlink prediction (链路预测). The process of...
In this paper, we provide a review of how such statistical models can be "trained" on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph). In particular, we discuss two fundamentally different kinds of ...
In this section, we first formally define the entity alignment problem on Knowledge Graphs (KGs), along with some related constraints. Then, we provide a qualitative comparison of entity alignment methods based on KG embedding. 2.1The entity alignment problem ...
4.6 RS on Multi-source Heterogeneous Graphs 5. Graph Learning Approaches to RS 5.1 Random Walk Approach 5.2 Graph Representation Learning Approach 5.3 Graph Neural Network Approach 5.4 Knowledge-Graph Approach 6. Open Reseearch Directions 最近在进行推荐系统入门,但是因为事情比较多,读得速度有点慢。这篇...
knowledge graphs, that empirical research and industrial application are still missing to a large extent, that graph embeddings are not fully exploited, and that technical literature is fast-growing but seems to be still far from its ... G Buchgeher,D Gabauer,J Martinez-Gil,... 被引量: 0...
The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a numb
Review Graph Mining A framework of review data mining based on a graph model. 3followers Japan https://rgmining.github.io/ README.md Repositories fraudarPublic A wrapper of FRAUDAR algorithm fraud-eaglePublic An implementation of Fraud Eagle algorithm ...
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