• Freebase

  • Referenced in 25 articles [sw27335]
  • structured general human knowledge. Freebase is a practical, scalable, graph-shaped database of structured general ... human knowledge, inspired by Semantic Web research and collaborative data communities such as the Wikipedia ... write access through an HTTP-based graph-query API for research, the creation and maintenance...
  • Pykg2vec

  • Referenced in 4 articles [sw30609]
  • Pykg2vec: A Python Library for Knowledge Graph Embedding. Pykg2vec is an open-source Python library ... entities and relations in knowledge graphs. Pykg2vec’s flexible and modular software architecture currently implements ... state-of-the-art knowledge graph embedding algorithms, and is designed to easily incorporate ... educational platform to accelerate research in knowledge graph representation learning. Pykg2vec is built...
  • OpenKE

  • Referenced in 4 articles [sw30611]
  • various fundamental models to embed knowledge graphs into a continuous low-dimensional space. OpenKE prioritizes ... support quick model validation and large-scale knowledge representation learning. Meanwhile, OpenKE maintains sufficient modularity ... embeddings of some existing large-scale knowledge graphs pre-trained by OpenKE are also available...
  • BioKEEN

  • Referenced in 3 articles [sw34085]
  • library for learning and evaluating biological knowledge graph embeddings. Knowledge graph embeddings (KGEs) have received ... predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem ... machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs...
  • AmpliGraph

  • Referenced in 2 articles [sw30610]
  • Library for Representation Learning on Knowledge Graphs. Open source library based on TensorFlow that predicts ... links between concepts in a knowledge graph. AmpliGraph is a suite of neural machine learning ... that deals with supervised learning on knowledge graphs. Use AmpliGraph if you need to: Discover ... from an existing knowledge graph.Complete large knowledge graphs with missing statements. Generate stand-alone knowledge...
  • ProjE

  • Referenced in 2 articles [sw34444]
  • ProjE: Embedding Projection for Knowledge Graph Completion. With the large volume of new information created ... validity of information in a knowledge graph and filling in its missing parts are crucial ... address this challenge, a number of knowledge graph completion methods have been developed using ... fills-in missing information in a knowledge graph by learning joint embeddings of the knowledge...
  • TransT

  • Referenced in 2 articles [sw34445]
  • Type-Based Multiple Embedding Representations for Knowledge Graph Completion. Knowledge graph completion with representation learning ... entity-relation triples from the existing knowledge graphs by embedding entities and relations into ... neglect semantic information contained in most knowledge graphs and the prior knowledge indicated...
  • DGL-KE

  • Referenced in 2 articles [sw34088]
  • Training Knowledge Graph Embeddings at Scale. Knowledge graphs (KGs) are data structures that store information ... machine learning tasks is to compute knowledge graph embeddings. DGL-KE is a high performance ... scalable package for learning large-scale knowledge graph embeddings. The package is implemented...
  • RotatE

  • Referenced in 2 articles [sw37755]
  • RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space. We study the problem ... representations of entities and relations in knowledge graphs for predicting missing links. The success ... present a new approach for knowledge graph embedding called RotatE, which is able to model ... model. Experimental results on multiple benchmark knowledge graphs show that the proposed RotatE model...
  • KEGGgraph

  • Referenced in 8 articles [sw06934]
  • KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor. Motivation: KEGG PATHWAY ... maps that represent current knowledge on biological networks in graph models. While valuable graph tools ... knowledge there is currently no software package to parse and analyze KEGG pathways with graph...
  • PyKEEN

  • Referenced in 2 articles [sw34084]
  • Python Library for Training and Evaluating Knowledge Graph Emebddings. Recently, knowledge graph embeddings (KGEs) received ... PyKEEN 1.0 enables users to compose knowledge graph embedding models (KGEMs) based on a wide...
  • TransG

  • Referenced in 2 articles [sw34443]
  • TransG : A Generative Mixture Model for Knowledge Graph Embedding. Recently, knowledge graph embedding, which projects ... fact triple. To the best of our knowledge, this ... first generative model for knowledge graph embedding, which is able to deal with multiple relation...
  • Vadalog

  • Referenced in 2 articles [sw33095]
  • Vadalog System: Datalog-based Reasoning for Knowledge Graphs. Over the past years, there has been ... today, such as reasoning over large knowledge graphs, Datalog has to be extended with features ... such as those required in advanced knowledge graphs. The Vadalog system is Oxford’s contribution...
  • Bio2RDF

  • Referenced in 10 articles [sw23946]
  • links within the warehouse. A knowledge map of the graph and descriptive statistics about...
  • KGDB

  • Referenced in 1 article [sw39248]
  • KGDB: knowledge graph database system with unified model and query language. Knowledge graph ... languages hinder the wider application of knowledge graphs. KGDB is a knowledge graph database system ... graphs, and meets the requirement of knowledge graph data storage and query load. (2) Using ... Cypher, which are two different knowledge graph query languages, and enables them to operate...
  • Biq Mac

  • Referenced in 73 articles [sw10532]
  • other approaches. In particular, for dense graphs, where linear programming-based methods fail, our method ... literature where, to the best of our knowledge, no other method is able...
  • Graph4Code

  • Referenced in 1 article [sw33949]
  • Graph4Code: A Machine Interpretable Knowledge Graph for Code. Knowledge graphs have proven extremely useful ... natural language understanding. Graph4Code is a knowledge graph about program code that can similarly power ... graphs in RDF to make the knowledge graph extensible by the community. We describe ... initial use cases of the knowledge graph in code assistance, enforcing best practices, debugging...
  • SemTK

  • Referenced in 1 article [sw26477]
  • Semantic Toolkit for Managing and Querying Knowledge Graphs. The relatively recent adoption of Knowledge Graphs ... benefiting from the power of Knowledge Graphs have few tools available for exploring, querying...
  • LibKGE

  • Referenced in 1 article [sw39398]
  • LibKGE - A knowledge graph embedding library for reproducible research. LibKGE ( https://github.com/uma-pi1/kge ... training, hyperparameter optimization, and evaluation of knowledge graph embedding models for link prediction ... analysis. LibKGE provides implementations of common knowledge graph embedding models and training methods...
  • KGAT

  • Referenced in 1 article [sw32568]
  • KGAT: Knowledge Graph Attention Network for Recommendation. To provide more accurate, diverse, and explainable recommendation ... work, we investigate the utility of knowledge graph (KG), which breaks down the independent interaction ... hybrid structure of KG and user-item graph, high-order relations --- which connect two items ... propose a new method named Knowledge Graph Attention Network (KGAT) which explicitly models the high...