NYU Faculty Digital Archive
metadata only
Unexpectedness as a Measure of Interestingness in Knowledge Discovery
Organizations are taking advantage of "data-mining" techniques to leverage the vast amounts of data captured as they process routine transactions. Data-mining is the process of discovering hidden structure or patterns in data. However several of the pattern discovery methods in datamining systems
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Would you mind being watched by machines? Privacy concerns in data mining#754385
- Group-based privacy preservation techniques for process mining#1092023
- Machine Learning and Principles and Practice of Knowledge Discovery in Databases#73429
- Intelligence cycle#767065
- Methodology for a Security/Dependability Adaptive Protection Scheme Based on Data Mining#295561
Record · ID 933268
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive