ITTC Project


Equation Discovery in Databases

Project Award Date: 0000-00-00



Description

With the growth in the storage of data in an electronically accessible form, increasing attention is being directed at how better to use this data. The overall process of extracting usable knowledge from electronically stored data is described as Knowledge Discovery in Databases. This process begins with data retrieval and results in consolidating and using the newly discovered knowledge in conjunction with existing knowledge. The part of the process where patterns are extracted or models are built is referred to as Data-Mining. This work concentrates on the Data Mining step of Knowledge Discovery in Databases. Knowledge Discovery in Databases is directly related to ITTC's core technical focus area of Intelligent Systems and Information Management, emphasizing the application of advanced, intelligent methodologies as applied to solving problems in information identification, retrieval, analysis, and fusion.

Many approaches can be used in Data Mining and many different kinds of patterns discovered or models built. This work focuses on one particular kind of model construction with wide applicability suitable for a particular set of characteristics of the data base. One model form widely used for both prediction and description is to represent the discovered patterns in a system of multivariable equations.

The proposed method to automatically induce models in the form of mathematical functions from data is applicable to data having the following characteristics:

1. High dimensionality of variables or attributes are of mixed types, numeric and symbolic.

2. Numerical equations to be discovered are multidimensional and homogeneous, that is to say, the same relationship does not hold over the entire problem domain. Different relationships hold in different parts of the problem space.

3. A model of numerical equations cannot be assumed a priori because the significant variables used in numerical equations are unknown before analysis.


The method combines a machine learning technique and regression analysis to automatically and intelligently help in discovery of knowledge hidden in data.


Investigators




Project Sponsors


Primary Sponsor(s): ITTC


Partner with ITTC

The Information and Telecommunication Technology Center at the University of Kansas has developed several assistance policies that enhance interactions between the Center and local, Kansas, or national companies. 

ITTC assistance includes initial free consulting (normally one to five hours). If additional support is needed, ITTC will offer one of the following approaches: 

Sponsored Research Agreement

Individuals and organizations can enter into agreements with KUCR/ITTC and provide funds for sponsored research to be performed at ITTC with the assistance of faculty, staff and students.

Licensing and Royalty/Equity Agreement

An ITTC goal is the development of investment-grade technologies for transfer to, and marketing by, local, Kansas, and national businesses. To enhance this process, the Center has developed flexible policies that allow for licensing, royalty, and equity arrangements to meet both the needs of ITTC and the company.

Commercialization Development

Companies with a technology need that can be satisfied with ITTC's resources can look to us for assistance. We can develop a relationship with interested partners that will provide for the development of a technology suited for commercialization.

ITTC Resource Access

ITTC resources, including computers and software systems, may be made available to Kansas companies in accordance with the Center's mission and applicable Regents and University policies.

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