Original Publication Date: 1997-Feb-01
Included in the Prior Art Database: 2005-Apr-01
Agrawal, R: AUTHOR [+4]
Disclosed is a method of an Intelligent Miner architecture and a brief description of the individual components.
a method of an Intelligent Miner architecture and
a brief description of the individual components.
A data mining
operation is typically made up of several
distinct steps combining the execution of data-mining kernels with
data processing functions. The user of the data-mining application
wants to be able to select and control the execution of these
functions in a flexible way.
The Intelligent Miner provides the means for this
control, and it features:
o A set of data-mining kernels providing the most frequently
required data mining technologies.
o A processing library providing functions like bulk load of
data and data transformation.
o A flexible way for read and write access to flat files and
relational database tables. This Application Processor
Interface (API) is only available to toolkit internal
functions, not to applications.
o A set of API functions to control the execution of the data
o A set of API functions to manage the results of data-mining
o A client/server structure to provide communications between
data mining and data processing functions on the server, and
administrative and visualization functions on the client.
o An Administration Graphical User Interface (Administration
GUI) to control the execution of the data-mining kernel and
processing functions and to manage the results of the
The main components shown in the Figure are:
o Administration Graphical User Interface (Administration GUI)
The Administration GUI provides the means for an end user to
specify input, output, and control parameters for the mining
kernels and data processing functions, as well as the
management of results.
o Processing Library
The Processing Library allows the user to collect and prepare
the input data from various databases.
o Environment Layer API
The Environment Layer API provides a set of data types and
classes to control the behavior of the data-mining kernels
and data processing functions. These classes are made
available as C++ classes that allow you to build applications
combining different functions.
o Client/Server Component
This component addresses the communication between data
types, client classes, and server classes. It is implemented
using Remote Procedure Calls (RPC).
Data Mining kernels
- Discovery of Associations
- Discovery of Sequential Patterns
- Discovery of Similar Time Sequences
- Prediction of a Classification
- Tree Induction
- Neural Induction