Method and a system for context based clustering of object

An object clustering system for context based clustering of objects comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor executable instructions, which on execution causes the processor to:
• receive an object clustering request for one or more objects associated with a plurality of contextual parameters, wherein the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes;
• tag the one or more non-physical attributes respectively to the one or more physical attributes;
• identify a common context from the one or more physical attributes associated with the one or more objects based on the tagging;
• map the one or more physical attributes to the one or more objects based on the common context;
• determine a mean value of the one or more physical attributes by generating a histogram, and a weightage is assigned to the one or more physical attributes;
• compute a variance value of the one or more physical attributes from the mean value of the histogram;
• and
• cluster the one or more objects based on the mapping when a distance of the variance value is lesser than a pre-defined distance with respect to the mean value.

A non-transitory computer-readable storage medium having stored thereon, a set of computer-executable instructions causing a computer comprising one or more processors to perform steps comprising:

• receive an object clustering request for one or more objects associated with a plurality of contextual parameters, wherein the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes;
• tag the one or more non-physical attributes respectively to the one or more physical attributes;
• identify a common context from the one or more physical attributes associated with the one or more objects based on the tagging;
• map the one or more physical attributes to the one or more objects based on the common context;
• and
• determine a mean value of the one or more physical attributes by generating a histogram, and a weightage is assigned to the one or more physical attributes;
• compute a variance value of the one or more physical attributes from the mean value of the histogram;
• and
• cluster the one or more objects based on the mapping when a distance of the variance value is lesser than a pre-defined distance with respect to the mean value.