Method and system for classification of web browsing history

A classification computing device comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor instructions, which, on execution, causes the processor to:
• receive the web browsing history from a web browser associated with a user, wherein the web browsing history comprises details about one or more web pages browsed by the user;
• extract one or more keywords from each of the one or more web pages browsed by the user based on a trained keyword dataset;
• determine a plurality of classifications for each of the one or more web pages based on the one or more keywords, wherein the plurality of classifications associated with each of the one or more webpages are determined by identifying common characteristics between the one or more keywords and parameters of each web browsing path using a trained classification dataset;
• generate a relevancy matrix between each of the one or more keywords of the one or more web pages and the corresponding plurality of classifications;
• and
• identify a classification from the plurality of classifications for each of the one or more webpages based on the relevancy matrix, wherein a snapshot of the classification is stored in a non-volatile storage unit of the web browser.

A non-transitory computer readable medium including instruction stored thereon that when processed by at least one processor cause a classification computing device to perform operations comprising:

• receiving the web browsing history from a web browser associated with a user, wherein the web browsing history comprises details about one or more web pages browsed by the user;
• extracting one or more keywords from each of the one or more web pages browsed by the user based on a trained keyword dataset;
• determining a plurality of classifications for each of the one or more web pages based on the one or more keywords, wherein the plurality of classifications associated with each of the one or more webpages are determined by identifying common characteristics between the one or more keywords and parameters of each web browsing path using a trained classification dataset;
• generating a relevancy matrix between each of the one or more keywords of the one or more web pages and the corresponding plurality of classifications;
• and
• identifying a classification from the plurality of classifications for each of the one or more webpages based on the relevancy matrix, wherein a snapshot of the classification is stored in a non-volatile storage unit of the web browser.