An architecture to support distributed data mining services in e-commerce environments
| Autor: | Arkady Zaslavsky, Seng Wai Loke, Shonali Krishnaswamy |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
ComputingMethodologies_SIMULATIONANDMODELING
Computer science business.industry Other information and computing sciences not elsewhere classified Application service provider Context (language use) E-commerce computer.software_genre World Wide Web Software agent Mobile agent Data mining Architecture Activity-based costing business Architectural model computer |
| Zdroj: | WECWIS |
| DOI: | 10.26180/20707846.v1 |
| Popis: | This paper presents our hybrid architectural model for Distributed Data Mining (DDM) which is tailored to meet the needs of e-businesses where application service providers sell DDM services to e-commerce users and systems. The hybrid architecture integrates the client-server and the mobile agent technologies. This model focuses on the optimisation and costing issues of DDM which are particularly relevant in the context of charging users for data mining services. The paper also presents a cost model for different DDM scenarios taking environmental factors into consideration. The cost model enables estimation of the DDM response time, thereby forming the basis for billing users. It also supports optimisation by determining analytically the best model for improving response time. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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