Data retrieval method, system and program product

• US 20040068493A1
• Filed: 09/24/2003
• Published: 04/08/2004
• Est. Priority Date: 10/04/2002
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kobayashi, Mei, Aono, Masaki
• Granted Patent: US 7,219,089 B2
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/358 Browsing; Visualisation therefor
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A data retrieval system having a database storing data as a vector that has been digitized based on a keyword. The system has capability of generating a residual vector from the data to compute a covariance matrix and an eigenvector of the covariance matrix. The system further has the capability for generating and storing a set of basic vectors from the set of the computed eigenvectors, and for reading out the data and at least one of the eigenvectors from a memory. This is utilized to compute a contribution of the eigenvector to the data, and for contracting or enlarging a residual vector to store. The system selects a keyword to be used for labeling according to a similarity between the stored basic vector and the data, and a weight on the similarity so as to store the keyword in a memory.

Claims

1. A data retrieval system for causing a computer to retrieve data being stored in a database, said retrieval system comprising:

a database storing data as a vector digitized based on a keyword;

a means for generating a residual vector from said data to compute a covariance matrix and an eigenvector of said covariance matrix, and for generating and storing a set of basic vectors from a set of said computed eigenvectors;

a means for reading out said data and at least one of said eigenvectors from a memory, and for computing a contribution of said eigenvector to said data, and for contracting or enlarging a residual vector to store; and

a means for selecting a keyword to be used for labeling according to a similarity between said stored basic vector and said data, and a weight on said similarity so as to store the keyword in a memory.

2. The data retrieval system according to claim 1, comprising a means for making said basic vectors orthogonal.

3. The data retrieval system according to claim 1, wherein said means for selecting the keyword to be used for labeling to store the keyword in the memory further comprises a means for determining the weight on said similarity to said keyword and a means for storing a certain number of keywords in a descending order in the memory in connection with said weight.

4. A data retrieval method for causing a computer to retrieve data stored in a database, said data retrieval method comprising the steps of:

reading out data from a database storing data as a vector digitized based on a keyword;

computing and storing a covariance matrix and an eigenvector of said covariance matrix, using said data;

generating and storing a set of basic vectors from a set of said computed eigenvectors;

reading out said data and at least one of said eigenvectors from a memory, and computing and storing a contribution of said eigenvector to said data; and

computing a residual vector from said data and said eigenvector, and contracting or enlarging a residual vector by reading out said contribution to compute and store a new eigenvector.

5. The data retrieval method according to claim 4, further comprising a step of selecting a keyword to be used for labeling from a similarity between said stored basic vector and said data and a weight on said similarity to store the keyword in the memory.

6. The data retrieval method according to claim 5, wherein said step of selecting the keyword to be used for labeling further comprises a step of determining the weight on said similarity to said keyword and storing a certain number of keywords in a descending order in the memory in connection with said weight.

7. A computer executable program for implementing a data retrieval method for causing a computer to retrieve data stored in a database, said program comprising the steps of:

reading out data from a database storing data as a vector digitized based on a keyword;

computing and storing a covariance matrix and an eigenvector of said covariance matrix, using said data;

generating and storing a set of basic vectors from a set of said computed eigenvectors;

reading out said data and at least one of said eigenvectors from a memory, and computing and storing a contribution of said eigenvector to said data; and

computing a residual vector from said data and said eigenvector, and contracting or enlarging a residual vector by reading out said contribution to compute and store a new eigenvector.

8. The program according to claim 7, further comprising a step of selecting a keyword to be used for labeling from a similarity between said stored basic vector and said data and a weight on said similarity to store the keyword in the memory.

9. The program according to claim 7, further comprising a step of making said basic vectors orthogonal before computing said residual vector.

10. A computer readable storage medium storing a computer executable program for implementing a data retrieval method for causing a computer to retrieve data stored in a database, said program comprising the steps of:

reading out data from a database storing data as a vector digitized based on a keyword;

computing and storing a covariance matrix and an eigenvector of said covariance matrix, using said data;

generating and storing a set of basic vectors from a set of said computed eigenvectors;

reading out said data and at least one of said eigenvectors from a memory, and computing and storing a contribution of said eigenvector to said data;

computing a residual vector from said data and said eigenvector, and contracting or enlarging a residual vector by reading out said contribution to compute and store a new eigenvector; and

generating and storing a set of basic vectors from a set of computed eigenvectors.

11. The storage medium according to claim 10, further comprising a step of selecting a keyword to be used for labeling from a similarity between said stored basic vector and said data and a weight on said similarity to store the keyword in the memory.

12. The storage medium according to claim 10, further comprising a step of making said basic vectors orthogonal before computing said residual vector.

13. A graphical user interface system for displaying the computer retrieved data, said graphical user interface system comprising:

a database storing data as a vector digitized based on a keyword;

a means for computing a basic vector from said data to store in a memory;

a means for classifying data into clusters depending on a similarity between said stored basic vector and said data, for counting the number of data included in said cluster, and for selecting a keyword to be used for labeling according to a weight on said similarity so as to store in a memory at least said number of data and said keyword as a pair; and

a means for displaying said cluster in spiral in order of the number of data of said cluster, and performing a different rendering processing for each adjacent cluster.

14. The graphical user interface system according to claim 13, wherein said means for computing the basic vector comprises a means for reading out said data and at least one of said eigenvectors from a memory, and computing and storing a contribution of said eigenvector to said data.

15. The graphical user interface system according to claim 13, wherein said means for displaying said cluster in spiral comprises a means for displaying the clusters from outside to inside in order of the clusters having a greater number of data.

16. A program for enabling a computer to implement a graphical user interface for displaying the computer retrieved data, said program comprising the steps of:

reading data from a database storing data as a vector digitized based on a keyword;

computing a basic vector from said data to store in a memory;

classifying data into clusters depending on a similarity between said stored basic vector and said data, for counting the number of data included in said cluster, and for selecting a keyword to be used for labeling according to a weight on said similarity so as to store in a memory at least said number of data and said keyword as a pair; and

displaying said cluster in spiral in order of the number of data of said cluster, and performing a different rendering processing for each adjacent cluster.

17. The program according to claim 16, wherein said step of computing the basic vector comprises a step of reading out said data and at least one of said eigenvectors from the memory, and computing and storing a contribution of said eigenvector to said data.

18. The program according to claim 16, wherein said step of displaying said cluster in spiral comprises a step of arranging the clusters from outside to inside in order of the clusters having a greater number of data.

19. A computer readable storage medium storing a program for enabling a computer to implement a graphical user interface for displaying the computer retrieved data, said program comprising the steps of:

reading data from a database storing data as a vector digitized based on a keyword;

computing a basic vector from said data to store in a memory;

classifying data into clusters depending on a similarity between said stored basic vector and said data, for counting the number of data included in said cluster, and for selecting a keyword to be used for labeling according to a weight on said similarity so as to store in a memory at least said number of data and said keyword as a pair; and

displaying said cluster in spiral in order of the number of data of said cluster, and performing a different rendering processing for each adjacent cluster.

20. The storage medium according to claim 19, wherein said step of displaying said cluster in spiral comprises a step of arranging the clusters from outside to inside in order of the clusters having a greater number of data.