Extracting knowledge from data
Knowledge extraction from data (KDE)
Article REF: H3744 V1
Extracting knowledge from data
Knowledge extraction from data (KDE)

Authors : Djamel Abdelkader ZIGHED, Ricco RAKOTOMALALA

Publication date: November 10, 2002 | Lire en français

Logo Techniques de l'Ingenieur You do not have access to this resource.
Request your free trial access! Free trial

Already subscribed?

5. Extracting knowledge from data

The modern approach to extracting knowledge from data is intended to be as general as possible. It favors neither a particular source of information (which may be locally stored or distributed), nor a specific type of data (which may be structured as attribute-values, texts of varying lengths, images or video sequences). It is not limited to the latest analysis tools, and explicitly incorporates methods for data preparation, analysis and validation of the knowledge produced. Most of these methods come from the fields of statistics, data analysis, machine learning and pattern recognition.

EDC is an anthropocentric process: the knowledge extracted must be as intelligible as possible for the user. It must be validated, formatted and organized. Let's take a closer look at all these notions and situate them within the overall EDC process.

EDC...

You do not have access to this resource.
Logo Techniques de l'Ingenieur

Exclusive to subscribers. 97% yet to be discovered!

You do not have access to this resource. Click here to request your free trial access!

Already subscribed?


Article included in this offer

"Software technologies and System architectures"

( 232 articles )

Complete knowledge base

Updated and enriched with articles validated by our scientific committees

Services

A set of exclusive tools to complement the resources

View offer details
Contact us