Peter logged in to ‘Amynra’, an eCommerce site. He wanted to grab some stuff for his impromptu bachelor party his friends planned. Peter doesn’t have a great way of online shopping as he rarely did it. For him, it was a maze of a plethora of products where he wanted to find his green, leafy, summery beach shorts! Indeed a task. So, he typed in ‘beach shorts’ and he was flooded with ‘Shorts’ of all types. Peter wasn’t ecstatic about the search results. He had to scroll deep and couldn’t find the ones he was searching for. He opts out. Now, imagine, how many ‘Peters’ actually do visit your website on a daily basis? And what if all of them kept opting out of your site every time? Showing relevant products based on shopper’s intent and history is the most important factor that you should integrate with your site. With so many websites and giants like Amazon and Flipkart in the market, there is no way you could find an escape with an average search engine. You need an on-point relevancy platform and an equally well-knit ranking system.
What, Why and How of Learning to Rank: Learning to Rank (LETOR) is used in the information retrieval (IR) class of problems, as ranking related