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OpenKE is a knowledge graph embedding framework designed to transform structured knowledge graphs into low-dimensional vector representations. It functions as a library for representation learning and a toolset for converting entities and relations into numerical embeddings. The project includes a link prediction engine to evaluate the likelihood of relationships between entities and identify missing facts in large-scale graphs. It provides a dedicated preprocessing tool to map raw entity and relation strings into numerical identifiers for machine learning training. The framework's capabilit
Starspace is a vector embedding framework designed for training high-dimensional representations of text and images. It functions as a machine learning system for neural ranking, text classification, and knowledge graph embedding, mapping different object types into a shared numerical space to facilitate retrieval and prediction tasks. The system includes specialized tools for knowledge graph completion and link prediction by representing entities and their relationships within a multi-relational vector space. It further provides capabilities for semantic content recommendation and large-scal
FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut
TuckER: Tensor Factorization for Knowledge Graph Completion
The main features of ibalazevic/tucker are: Knowledge Graph Embeddings, Geometric Deep Learning: Graph & Irregular Structures.
Open-source alternatives to ibalazevic/tucker include: ibalazevic/hyper — Hypernetwork Knowledge Graph Embeddings. thunlp/openke — OpenKE is a knowledge graph embedding framework designed to transform structured knowledge graphs into low-dimensional… facebookresearch/starspace — Starspace is a vector embedding framework designed for training high-dimensional representations of text and images.… dmlc/dgl — DGL is a Python library for building and training graph neural networks. It functions as a graph message passing… falkordb/falkordb — FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge… benedekrozemberczki/clustergcn — A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional…
