Advanced · Data
Knowledge extraction
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. Knowledge extraction creates machine-readable knowledge from structured or unstructured data, going beyond simple information retrieval.
Technical Definition
Knowledge extraction creates machine-readable knowledge from structured or unstructured data, going beyond simple information retrieval.
How it works
Knowledge extraction focuses on deriving structured, machine-interpretable knowledge from various data sources, including text, databases, and images. Unlike standard data processing, the goal is to create knowledge that facilitates inferencing and deeper understanding. This process often involves natural language processing and information retrieval techniques.
Related Concepts
- Ontology — A formal specification of the concepts, properties, and relationships in a domain.
- Knowledge representation and reasoning (KR² or KR&R) — Knowledge Representation and Reasoning (KR&R) is the AI field focused on how computers can store and use knowledge to solve problems.
- Natural language processing (NLP) — A field of AI enabling computers to understand, interpret, and generate human language.
- Information Extraction (IE) — Automatically identifying and extracting structured information from unstructured or semi-structured text.