Call For Paper Volume:4 Issue:10 Oct'2017 |

Information Compression of Big Data using the SP Theory of Intelligence

Publication Date : 30/04/2015



Author(s) :

Vishmitha , Prof. B. S. Umashankar.


Volume/Issue :
Volume 2
,
Issue 4
(04 - 2015)



Abstract :

Big data includes large quantity of data that results drawbacks both in accessing and managing the data. These drawbacks are overcome by the introduction of the SP theory of Intelligence. The term ‘SP’ indicates ‘Simplicity’ and ‘Power’. The central theme used in the theory is lossless information compression. This helps in making the big data small, thereby provides benefits both in accessing and management. The purpose of this project is to overcome the problems in big data using the SP Theory of Intelligence. In order to achieve this goal, big data is subjected to clustering and compression techniques. Compression of information is achieved by pattern matching. Using such a system leads to the improvement in the processing of big data. The SP Theory provides pattern recognition, information storage, retrieval and information compression. Although this theory leads in faster information retrieval, the integrity of the original information is maintained. Future work has to be done in this area to work with patterns in two dimensions.


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Information Compression of Big Data using the SP Theory of Intelligence

May 1, 2015