Knowledge extraction is the process of deriving structured knowledge from data, text, databases, logs, or other information sources. It often identifies entities, relationships, events, rules, or patterns for use in knowledge graphs, expert systems, or analytics.
The creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or