Remote collaborative data mining through online knowledge sharing

• Type: Article in International Conference Proceedings Book
• Date: 2002

Authors

Jorge, A (Author) FEP; Moyle, S (Author) Other; Voss, A (Author) Other

Conference proceedings International

Title: COLLABORATIVE BUSINESS ECOSYSTEMS AND VIRTUAL ENTERPRISES

Pages: 497-504

3rd Working Conference on Infrastructures for Virtual Enterprises (PRO-VE 02)

SESIMBRA, PORTUGAL, MAY 01-03, 2002

Indexing

ISI Web of Knowledge - 1 Citation

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-000-QZP

Abstract (EN): The basic principles of a methodology for remote collaborative data mining are proposed. Starting from CRISP-DM, a general data mining process designed to carry out data mining projects; it is described how the principles of knowledge sharing and ease of communication can be embedded in the data mining process, The aim is to allow the execution of data mining projects, with the participation of multiple experts working from distant locations. All the participants in such a project can profit from the knowledge produced by others and share their knowledge online with the other participants. The produced knowledge (for example data transformations, working hypothesis, models, results of experiments) is also stored for future inspection and use, in pursuit of organizational learning. A prototypical implementation (RAMSYS) of the remote collaborative methodology is described with examples.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8