METHOD AND SYSTEM FOR DISCOVERY AND MODIFICATION OF DATA CLUSTER AND SYNONYMS

• US 20090182755A1
• Filed: 01/10/2008
• Published: 07/16/2009
• Est. Priority Date: 01/10/2008
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Hunt, Brand Lee, Adair, Gregery Gene
• Granted Patent: US 7,962,486 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/285 Clustering or classification

Abstract

Discovery and modification of data clusters such as synonyms. In one aspect, a method for clustering data includes receiving information on a system, the information manipulating one or more data attributes stored or to be stored in a database accessible by the system, where the information and manipulation does not explicitly relate to data clusters. A data cluster is automatically adjusted based on the received information, the data cluster including multiple data attributes and including at least one of the data attributes manipulated by the received information. The data cluster is adjusted dynamically and in response to the information being received.

Claims

1. A method for clustering data, the method comprising:

receiving information on a system, the information manipulating one or more data attributes stored or to be stored in a database accessible by the system, wherein the information and manipulation does not explicitly relate to data clusters; and

automatically adjusting a data cluster based on the received information, the data cluster including a plurality of data attributes and including at least one of the data attributes manipulated by the received information, wherein the data cluster is adjusted dynamically and in response to the information being received.

2. The method of claim 1 wherein the received information includes one or more received data attributes to be stored in the database with stored data accessible by the system, wherein the adjusted data cluster is a new data cluster and the adjusting includes discovering and forming the new data cluster to include at least one of the received data attributes.

3. The method of claim 1 wherein the adjusted data cluster is an existing stored data cluster accessible by the system and the adjusting includes modifying the existing data cluster.

4. The method of claim 3 wherein the modifying includes removing at least one data attribute from the existing data cluster based on the received information and based on the current data in the database.

5. The method of claim 4 wherein the received information includes one or more received data attributes to be stored in the database with stored data accessible by the system, and wherein removing the at least one data attribute from the existing data cluster includes determining that the removed at least one data attribute has become generic.

6. The method of claim 1 wherein the data cluster is adjusted based on the current number of occurrences of at least one of the manipulated data attributes in the database.

7. The method of claim 1 wherein a plurality of stored existing data clusters are accessible by the system, wherein the existing data clusters only include data attributes that were manipulated by past information received by the system, the past information not specifically related to data clusters.

8. The method of claim 7 wherein the plurality of existing data clusters are stored in a table and are modified dynamically in response to the information being received.

9. The method of claim 1 wherein the data cluster is a synonym for use in finding at least one candidate entity from a plurality of entities stored by the database, each candidate entity having a plurality of associated data attributes.

10. The method of claim 1 wherein the plurality of data attributes in the data cluster are of a plurality of different types.

11. The method of claim 1 wherein the received information includes one or more received data attributes to be stored in the database with stored data accessible by the system, and wherein adjusting the data cluster includes:

finding a plurality of stored existing data clusters that include at least one of the received data attributes;

finding a plurality of candidate data entities that each include one or more of the existing data clusters and a plurality of candidate data entities that each include any of the plurality of received data attributes not included in the existing data clusters; and

determining whether any data attributes should be removed from the existing data clusters based on the candidate data entities and the received information.

12. The method of claim 11 wherein adjusting the data cluster further comprises determining that a plurality of the received data attributes form a new data cluster, wherein the received data attributes in the new data cluster appear in a threshold percentage number of the candidates that include at least one of the received data attributes in the new data cluster, and further comprising adding the new data cluster to each of the candidate data entities that include the data attributes in the new data cluster.

13. The method of claim 11 wherein adjusting the data cluster further comprises determining that at least one of the received data attributes is to be added to an existing data cluster in the received information, wherein the at least one added data attribute and existing synonym appear in a threshold percentage number of candidate data entities that include at least one of the received data attributes in the existing data cluster or include the at least one received data attribute to be added.

14. The method of claim 11 wherein determining whether any attributes should be removed from existing data clusters includes determining whether the number of candidate data entities has fallen below a threshold percentage number of candidate data entities based on the received data attributes.

15. The method of claim 11 further comprising adding a new data cluster or removing a existing data cluster from at least one adjusted candidate data entity, and evaluating the data attributes of the at least one adjusted candidate data entity to check whether the at least one adjusted data cluster has updated data clusters.

16. A method for clustering data, the method comprising:

receiving information on a system, the information including a plurality of received data attributes to be stored in at least one data entity in a database accessible by the system; and

modifying one or more data clusters based on the received information, each of the one or more data clusters including a plurality of data attributes and including at least one of the received data attributes, wherein the modifying includes removing a particular data attribute from the one or more data clusters.

17. The method of claim 16 wherein the removing of the data attributes is performed in response to determining that the received information reduces below a predetermined threshold the percentage of candidate data entities in the database that currently have the particular data attribute.

18. The method of claim 16 wherein modifying the one or more data clusters includes:

finding a plurality of stored existing data clusters that include at least one of the received data attributes;

finding a plurality of candidate data entities that include the existing data clusters and a plurality of candidate data entities that include any of the plurality of received data attributes not included in the existing data clusters; and

determining whether any data attributes should be removed from existing data clusters based on the candidate data entities and the received information.

19. A method for discovering synonyms, the method comprising:

receiving information on a system, the information including a plurality of received data attributes associated with a particular data entity having data attributes stored in a database, the received data attributes to be stored in one or more data entities stored in the database, wherein the information and data attributes do not explicitly relate to synonyms; and

automatically forming a synonym based on the received data attributes and based on the currently stored data, the synonym including a plurality of the received data attributes associated with the data entity, wherein the forming includes examining a plurality of candidate data entities in the database which include at least one of the received attributes, and wherein the synonym is formed dynamically and in response to the information being received.

20. The method of claim 19 wherein the forming the synonym includes:

determining whether the one or more of the received data attributes appear with other received data attributes sufficiently frequently in different data entities to form a synonym from the appearing data attributes.

21. A computer readable medium storing program instructions to be executed by a computer and for clustering data, the program instructions performing steps comprising:

receiving information on a system, the information manipulating one or more data attributes stored in a database accessible by the system, wherein the information and manipulation does not explicitly relate to data clusters; and

automatically adjusting a data cluster based on the received information, the data cluster including a plurality of data attributes and including at least one of the data attributes manipulated by the received information, wherein the data cluster is adjusted dynamically and in response to the information being received.

22. The computer readable medium of claim 21 wherein the received information includes one or more received data attributes to be stored in the database with stored data accessible by the system, wherein the adjusted data cluster is a new data cluster and the adjusting includes discovering and forming the new data cluster to include at least one of the received data attributes.

23. The computer readable medium of claim 21 wherein the adjusted data cluster is an existing stored data cluster accessible by the system and the adjusting includes removing at least one data attribute from the existing data cluster based on the received information and based on the current data in the database.

24. The computer readable medium of claim 21 wherein the data cluster is adjusted based on the current number of occurrences of at least one of the manipulated data attributes in the database.

25. A system for clustering data, the system comprising:

a database storing a plurality of data entities, each data entity including a plurality of stored data attributes;

means for receiving information on a system, the information manipulating one or more of the stored data attributes or one or more data attributes stored in the received information, wherein the information and manipulation does not explicitly relate to data clusters; and

means for automatically adjusting a data cluster based on the received information, the data cluster including a plurality of data attributes and including at least one of the data attributes manipulated by the received information, wherein the data cluster is adjusted dynamically and in response to the information being received.