The full text of this article

 

Multiagent-based processing and integration of system data
by Khamisi Kalegele; Johan Sveholm; Hideyuki Takahashi; Kazuto Sasai; Gen Kitagata; Tetsuo Kinoshita
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 12, No. 2, 2013

 

Abstract: This paper presents a multiagent-based ETL (Extract, Transform, Load) unit for the processing and integration of system operational data in order to improve its value. Operational data plays a vital role in managing and optimising systems. Although KDD (Knowledge Discovery and Data Mining) techniques and concepts have long existed, it is only now that we are seeing real applications being extended onto network and systems management. However, the massive data pre-processing (e.g. feature extraction and data integration) which is needed prior to putting KDD tools in action, is still limiting the extent of exploitation. We propose and design the multiagent-based ETL unit which uses Support Vector Machine and Natural Language Processing techniques to efficiently extract information features from operational data. The unit uses an mSPIDER algorithm to discover INclusion Dependencies (INDs) which are used to integrate data across its peers within the system. We demonstrate efficiency of the unit and the used approaches using operational data from a mailing system.

Online publication date: Fri, 30-Aug-2013

 

is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

 
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

 
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

 

    Username:        Password:         

Forgotten your password?


 
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

 
If you still need assistance, please email subs@inderscience.com