Extracting supplier information from the web

Using web crawling technology in coordination with state of the art machine learning techniques, the project aims to mine useful, structured information about the world’s suppliers from the web. Recent advances in artificial intelligence have increased the viability of such autonomous systems for extracting coherent information from arbitrary human-produced content. By leveraging these technologies, our goal is to build improved supplier discovery and recommendation systems. Such systems would enable manufacturers to meet the right suppliers faster, thus putting their products on the market sooner. The methods and processes we will develop might be transferable to different text mining tasks on other subjects as well.

Intern: 
Mete Kemertas
Faculty Supervisor: 
Frank Rudzicz
Province: 
Ontario
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