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Ten Grade Student Of Indian-origin claims his search engine is 47% more accurate than Google.

Imagine an innovation school project that claims to be 47% search accuracy than Google’s search engine. 

A Sixteen-year-old Anmol Tukrel, who is of an Indian-origin with  Canadian citizenship has already developed very personalized search engine that has high accuracy than Google ( about 47%), and has about 21% more accuracy on an average search keywords.

Anmol Tukrel

                                           Anmol Tukrel

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Tukrel, didn’t take more than a couple of months for the design, and took merely 60 hours to code the search engine, for a project to be submitted at the prestigious Google Science Fair, which is a global online competition in which students aged between 13 years to 18 years participate.
Tukrel’s developing kit includes a computer with 1 gigabyte of free storage space, a python-language development environment, a spreadsheet program and access to Google and New York Times.

“I thought i might do one thing within the personalised search domain. It had been the foremost genius factor ever.However once I realised Google already done it , I attempted taking it to following upper level,” said Tukrel.

Tukrel was in India in Bengaluru for a two week long Internship.
To test the accuracy of his unique computer programme, he restricted his search question to the present year’s news articles from The NY Times. He created many fictitious users with totally different interests and corresponding internet histories. Tukrel then fed this data to each Google and his interest-based computer programme. Finally, the results were compared.

Ten Grade Student Of Indian-origin claims his search engine is 47% more accurate than Google.

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Today, personalization depends on factors like one’s location, browsing history, and also the affinity to the sort of apps they install on their phone. that is only 1 a part of the equation. Tukrel claims his formula solves the opposite aspect of the equation: It understands what a user would love before it serves up the results by domicile deep into the content of the text, understanding the underlying which means, before matching it to a user’s temperament, and throwing up the result.

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Hats Off To This Genious