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Evaluation of Meta-Benchmarking Practices of
Distributed Data Mining to Facilities Management
Ezendu I. Ariwa
Department of Accounting, Banking & Financial Systems
London Metropolitan University, UK
Mohamed M. Medhat
Sadat Academy for Management Sciences, Egypt
Distributed data mining [DDM] has great functionalities that can offer
to nowadays applications. That is because the nature of most of these
applications is data distribution. One of the potential applications for
distributed data mining is the use of OIKI DDM model in Facilities
Management (FM). In this paper we investigate the potential
advantages of this approach.
Keywords: Information Systems [IS] – Facilities Management [FM] –
Knowledge Discovery – OIKI DDM – Decision Support System [DSS] –
Meta-Intelligent – Informatization – Financial Engineering [FE].
1- Introduction
There is no agreed definition on the term “Facilities Management” in
the literature. However we could define it as follows: Facilities
maintaining, improving and adapting the infrastructure of an
organization in order to build an environment that strongly supports
the primary objectives of the organization. The FM uses information in
order to accomplish its task. This information inherently distributed
among a number of heterogeneous databases in different loosely
coupled sites connected by a computer network [5].
Distributed data mining refers to the mining of distributed data sets.
The data sets are stored in local databases, hosted by local
computers, which are connected through a computer network. Data
mining takes place at a local level and at a global level where local
data mining results are combined to gain global findings [11].
In some applications, data are inherently distributed, but it is
necessary to gain global insights from the distributed data sets. For
example, each site of a multinational company manages its own
operational data locally, but the data must be analyzed for global
marketing, and sales. One of the direct applications of distributed
data mining is the use of it in FM in order to improve the decision
making process.
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