datamined

Datamined is the past participle and adjective form used to describe information or assets that have been obtained by applying data mining techniques to large datasets or collections. Datamined data or assets are not typically released by the data owner; instead they are discovered through analysis of raw files, logs, databases, or software packages.

Data mining involves computational methods to discover patterns, correlations, and insights. Techniques include statistical analysis, clustering, classification, association rules, and machine learning. The term datamined often describes content that has been extracted from a source such as a game, app, or hardware firmware, sometimes including unreleased features, content, or metadata.

Applications and contexts: In software and video game communities, datamining is used to identify unreleased content, changes in patches, or hidden parameters. In business and science, datamining contributes to discovering trends, anomalies, or predictive models.

Ethical and legal considerations: Datamining can raise privacy concerns when sensitive data is involved. Respect for terms of service and licenses is important; extracting data from proprietary software may violate agreements or laws. Datamined information can be speculative and incomplete or intentionally misleading.

Limitations: Data quality, access restrictions, and incomplete datasets can affect reliability. Findings should be corroborated with official sources when possible.

See also: Data mining, Data science, Reverse engineering, Information extraction.