4 dépôts
Mechanisms for locating nodes within a specific number of hops or a defined distance from a seed node.
Distinct from Isolated Node Discovery: The candidates focus on network cluster discovery or statistical outliers, not graph hop-distance discovery.
Explore 4 awesome GitHub repositories matching data & databases · Distance-Based Node Discovery. Refine with filters or upvote what's useful.
LogicStack-LeetCode is a curated repository of solved algorithm problems and data structure implementations, primarily drawn from the LeetCode platform. Its core identity is a structured collection of solutions designed to support technical interview preparation and competitive programming practice, with each solution accompanied by complexity analyses to help engineers understand performance trade-offs. The repository distinguishes itself through its breadth of coverage across fundamental algorithmic patterns and data structures. It includes implementations for array manipulation, string pro
Implements algorithms for finding all nodes exactly K hops away from a target node in a tree.
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
The product locates nodes at a specific distance from a starting point via relationship filters.
Ce projet est une bibliothèque d'algorithmes de data mining et une implémentation de référence pour le machine learning. Il fournit une collection d'outils pour effectuer la classification, le clustering et l'exploration de règles d'association, ainsi qu'une boîte à outils pour l'optimisation inspirée de la nature. La bibliothèque inclut des utilitaires spécialisés pour l'exploration de graphes et de séquences, permettant l'extraction de sous-graphes fréquents et de modèles séquentiels. Elle dispose également d'un utilitaire de réduction de dimensionnalité qui utilise la théorie des ensembles approximatifs (rough set theory) pour supprimer les attributs redondants des jeux de données. Le projet couvre un large éventail de capacités analytiques, notamment l'analyse de réseaux et de graphes pour classer l'importance des nœuds, ainsi que l'utilisation de modèles probabilistes et d'arbres de décision pour la classification des données. Il implémente également des méthodes basées sur la distance et la densité pour le regroupement de données et des modèles de recherche heuristiques pour résoudre des problèmes d'optimisation complexes.
Evaluates the importance of nodes in networks using structural ranking and link analysis.
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
Measures structural importance of nodes using shortest-path distances for stable entity ranking.