Automatic data explorer that determines relationships among original and derived fields

• US 20020128998A1
• Filed: 05/15/2001
• Published: 09/12/2002
• Est. Priority Date: 03/07/2001
• Status: Abandoned Application

• Current Assignee: Loyola Marymount University
• Original Assignee: Loyola Marymount University
• Inventors: Gregory, Brian, Kil, David
• Application Number:
  US09/858,927
• Publication Number:
  US 20020128998A1
• Time in Patent Office: Days
• US Class Current: 707/1
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases

Abstract

An automatic data mining tool that characterizes the relationships between different database fields from both structured and unstructured data. It extracts a data model, identifies and categorizes all the data fields, performs pre-processing to deal with unstructured data effectively, and processes the data without human intervention to automatically explore how the fields are related to one another. Prior to the commencement of user-controlled data mining, the present invention goes through all the fields in a database table space in order to establish meaningful relationships between various fields using whatever computer resources are available (i.e. by using “cycle stealing”). This allows the present invention to run in the background and establish relationships between fields even before data mining (DM) begins, and determine redundant, useless, and/or trivial fields without any external guidance. This results in faster, more accurate data mining since these relationships are available before a user begins the process of data mining.

Claims

1. A method for improving the efficiency of data mining software tools that operate on a database, the method comprising:

determining relationships between tables in the database;

identifying and categorizing all data fields in the tables;

pre-processing any unstructured data fields to represent the unstructured fields with vectors compatible with a format of structured fields;

converting certain fields into modified fields;

determining a level of relationship between all the data fields; and

storing the relationship data in a database;

wherein the method is performed automatically by a computer system when system resources are available, and without human intervention.

2. The method of claim 1, wherein determining a level of relationship comprises determining one of a level of correlation, discrimination and association.

3. The method of claim 1, wherein determining a level of relationship comprises determining a level of correlation, discrimination and association.

4. A method for determining relationships among data fields in a database, the method comprising:

extracting a data model for each set of related tables in the database;

determining whether each field in each table is structured or unstructured data;

for each unstructured data field, determining a data type for each field;

extracting feature data from the unstructured data based upon the determined data type of the data fields;

analyzing the structured fields and feature data to determine a level of relationship between the fields or data; and

storing information related to the level of relationship between the fields or data.

5. The method of claim 4, wherein determining a level of relationship comprises determining one of a level of correlation, discrimination and association.

6. The method of claim 4, wherein determining a level of relationship comprises determining a level of correlation, discrimination and association.

7. The method of claim 4, wherein the method is performed on the database data prior to a user commencing a data mining operation.

8. The method of claim 7, wherein the method is performed automatically by a computer system when system resources are available.

9. The method of claim 8, wherein analyzing the structured fields and feature data further comprises performing one of compression, energy compaction, anomaly, ergodicity, moments, insights and anachronism analysis.

10. The method of claim 9, wherein extracting feature data comprises performing a mathematical transform on the unstructured data.

11. A computer readable medium including computer code for an automatic data explorer that determines relationships among original and derived fields, the computer readable medium comprising:

computer code for extracting a data model for each set of tables in the database;

computer code for determining whether each field is structured or unstructured data;

computer code for determining a data type for each unstructured field;

computer code for extracting feature data from the unstructured data based upon the determined data type of the data fields;

computer code for analyzing the structured fields and feature data to determine a level of relationship between the fields or data; and

computer code for storing information related to the level of relationship between the fields or data..

12. The computer readable medium of claim 11, wherein the computer code for determining a level of relationship comprises computer code for determining one of a level of correlation, discrimination and association.

13. The computer readable medium of claim 11, wherein the computer code for determining a level of relationship comprises computer code for determining a level of correlation, discrimination and association.

15. The computer system of claim 14, further comprising computer code for converting certain fields into modified fields, prior to determining a level of relationship between all the data fields.

16. The computer system of claim 14, wherein the computer code for determining a level of relationship comprises computer code for determining one of a level of correlation, discrimination and association.

17. The computer system of claim 14, wherein the computer code for determining a level of relationship comprises computer code for determining a level of correlation, discrimination and association.

14. A computer system for improving the efficiency of data mining software tools that operate on a database, the computer system comprising:

a processor; and

computer program code that executes on the processor, the computer program code comprising;

computer code for determining relationships between tables in the database;

computer code for identifying and categorizing all data fields in the tables;

computer code for pre-processing any unstructured data fields to represent the unstructured fields with vectors compatible with a format of structured fields;

computer code for determining a level of relationship between the all the data fields, and

computer code for storing the relationship data in a database;

wherein the computer code is executed automatically by the computer system when system resources are available, and without human intervention..