rahulnyk/knowledge_graph

Features

• Knowledge Graph Extraction - Transforms unstructured text into structured knowledge representations by identifying entities and their semantic relationships.
• Entity Extraction Pipelines - Provides an automated pipeline that uses local language models to parse raw text into structured nodes and edges.
• Knowledge Graph Construction - Automates the build process of graph structures from unstructured text datasets.
• Local Model Inference Servers - Hosts language models locally to process documents while ensuring data privacy and minimizing latency.
• Text-to-Graph Transformers - Converts unstructured text corpora into structured property graphs using local language models.
• Knowledge Graph Builders - Builds structured knowledge graphs from raw text by extracting organized facts and triples.
• Semantic Networks - Implements a graph-based memory structure using nodes and edges to store concepts and their semantic relationships.
• Graph Node Clustering - Groups graph nodes into clusters based on structural similarity to understand community distribution.
• Graph-Based Retrieval Engines - Uses a knowledge graph engine to improve the accuracy of information retrieval from unstructured documents.
• Semantic Topology Mapping - Calculates node degrees and identifies community clusters to determine the size and color of visual graph elements.
• Semantic Traversals - Enables information retrieval by traversing semantic connections between entities instead of relying on keyword searches.
• Graph Topology Analysis - Identifies key clusters and influential nodes by calculating centrality metrics to understand data distribution.
• Graph-Based Retrieval - Finds specific information within a dataset by traversing a network of related nodes.
• Interactive Graph Visualizers - Renders interactive directed graphs in a browser environment for analyzing complex data relationships.
• Interactive Visualization Rendering - Provides an interactive web interface for rendering dynamic semantic networks that update based on user navigation.
• Semantic Graph Analyzers - Calculates node degrees and performs community detection to determine the visual properties of network elements.

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