SYSTEM AND METHOD OF GENERATING INITIAL CLUSTER CENTROIDS

• US 20160275169A1
• Filed: 03/17/2015
• Published: 09/22/2016
• Est. Priority Date: 03/17/2015
• Status: Abandoned Application

• Current Assignee: Infoutpia Co., Ltd.
• Original Assignee: Infoutpia Co., Ltd.
• Inventors: LEE, Tsung-Hsiung, CHIU, I-Hsun
• Application Number:
  US14/660,127
• Publication Number:
  US 20160275169A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 18/23213 with fixed number of clusters, e.g. K-means clustering
• CPC Class Codes: G06F 18/24137 Distances to cluster centroïds

Abstract

A computer system includes a processor and a computer-readable storage medium. The computer-readable storage medium has stored therein instructions that when executed by the processor perform a method for generating initial cluster centroids. The method includes generating (Key1, Value1) pairs of input datasets. The method also includes calculating global designated values, among the generated (Key1, Value1) pairs, to be reference values. The method also includes calculating similarity values of the input datasets based on the reference values. The method further includes generating (Key2, Value2) pairs of input datasets. The method further includes generating median similarity value, among the generated (Key2, Value2) pairs, to generate corresponding initial cluster centroids. The Key1 and the Value1 are a feature variable and a feature value, respectively, of corresponding input dataset. The Key2 and the Value2 are the similarity value and the feature value, respectively, of corresponding input dataset.

Claims

1. A method of generating initial cluster centroids using a processor, comprising:

using the processor, generating (Key1, Value1) pairs of input datasets;

using the processor, calculating global designated values, among the generated (Key1, Value1) pairs, to be reference values;

using the processor, calculating similarity values of the input datasets based on the reference values; and

using the processor, generating median similarity values based on the similarity values of the input datasets to generate corresponding initial cluster centroids,

wherein

the Key1 and the Value1 are a feature variable and a feature value,

respectively, of corresponding input dataset;

the processor runs the steps of generating (Key1, Value1) pairs, the steps of calculating global designated values, the steps of calculating similarity values and the steps of generating median similarity values by executing a set of instructions storing in a machine readable storage medium.

2. The method of claim 1, wherein the steps of generating (Key1, Value1) pairs, the steps of calculating global designated values, the steps of calculating similarity values and the steps of generating median similarity value are performed using MapReduce processes.

3. The method of claim 1, wherein the global designated values are global minimum values of corresponding input datasets.

4. The method of claim 1, wherein the global designated values are global maximum values of corresponding input datasets.

5. The method of claim 1, wherein a distance formula is used to calculate the similarity values.

6. The method of claim 1, further comprising generating, using the processor, (Key2, Value2) pairs of input datasets, wherein the Key2 and the Value2 are the similarity value and the feature value, respectively, of corresponding input dataset;

7. The method of claim 6, further comprising sorting, using the processor, the (Key2, Value2) pairs of input datasets in an increasing order based on respective “

Key2”

values.

8. The method of claim 7, further comprising dividing, using the processor, the (Key2, Value2) pairs of input datasets into N groups for N corresponding clusters such that the median similarity values are generated for each of N groups.

9. A computer program product tangibly embodied in a machine readable storage medium and comprising instructions that when executed by a processor perform a method for generating initial cluster centroids, the method comprising

calculating global designated values, among a plurality of input datasets, to be reference values;

calculating similarity values of the plurality of input datasets based on the reference values; and

generating median similarity values based on the similarity values of the plurality of input datasets to generate corresponding initial cluster centroids.

10. The computer program product of claim 9, further comprising generating (Key1, Value1) pairs of the plurality of input datasets such that the global designated values are generated based on the (Key1, Value1) pairs, wherein the Key1 and the Value1 are a feature variable and a feature value, respectively, of corresponding one of the plurality of input dataset.

11. The computer program product of claim 9, further comprising generating (Key2, Value2) pairs of the plurality of input datasets such that the median similarity values are generated based on the (Key2, Value2) pairs, wherein the Key2 and the Value2 are the similarity value and the feature value, respectively, of corresponding one of the plurality of input dataset;

12. The computer program product of claim 9, wherein the steps of calculating global designated values, the steps of calculating similarity values and the steps of generating median similarity value are performed using MapReduce processes.

13. The computer program product of claim 9, wherein the global designated values are global minimum values in the plurality of input datasets.

14. The computer program product of claim 9, wherein the global designated values are global maximum values in the plurality of input datasets.

15. The computer program product of claim 9, wherein a distance formula is used to calculate the similarity values.

16. The computer program product of claim 11, further comprising sorting the (Key2, Value2) pairs of input datasets in an increasing order based on respective “

Key2”

values.

17. The computer program product of claim 11, further comprising dividing the (Key2, Value2) pairs of input datasets into N groups for N corresponding clusters such that the median similarity values are generated for each of N groups.

18. A computer system comprising:

a processor; and

a computer-readable storage medium having stored therein instructions that when executed by the processor perform a method for generating initial cluster centroids, the method comprising;

generating (Key1, Value1) pairs of input datasets;

calculating global designated values, among the generated (Key1, Value1) pairs, to be reference values;

calculating similarity values of the input datasets based on the reference values;

generating (Key2, Value2) pairs of input datasets; and

generating median similarity value, among the generated (Key2, Value2) pairs, to generate corresponding initial cluster centroids,

wherein

the Key1 and the Value1 are a feature variable and a feature value,

respectively, of corresponding input dataset;

the Key2 and the Value2 are the similarity value and the feature value,

respectively, of corresponding input dataset.

19. The computer system of claim 18, wherein the step of generating (Key1, Value1) pairs, the steps of calculating global designated values, the steps of calculating similarity values, the step of generating (Key2, Value2) pairs and the steps of generating median similarity value are performed using MapReduce processes.

20. The computer system of claim 18, wherein the global designated values are global minimum values in the input datasets.