Glimpses On Implicit/Explicit, Dense/Sparse, Gated/Non Gated, Low Rank And Many More Layered Interactions Neural ranking models are the most important component in multi stage retrieval and ranking pipeline. Whether it is e-commerce search, ads targeting, music search or browse feed ranking, ranking model will have the final say in selecting…

Context : This document discusses the high level architecture and components required to create a model prediction service. Here we won’t be discussing and comparing particular frameworks in detail. The underlined intention is to provide a holistic view of model serving pipelines, APIs needed and complexities involved. …

Consider a typical e-commerce product. It would have a variety of content specific features like product title, brand, thumbnail etc and other engagement driven features like number of clicks, click through rate etc. Any machine learning model ingesting features of this product(e.g. product ranker, recommendation model etc.) would have to…

Introduction: The journey of a search query through e-commerce engineering stack can be broadly divided into following phases, search query text processing phase, retrieval phase where relevant products are fetched from indexer and the last but not the least, product re-ranking phase where a machine learning ranking engine re sorts the…

Real-time bidding(RTB) refers to the buying and selling of online ad impressions through real-time auctions that occur in the time it takes a webpage to load. Those auctions are often facilitated by ad exchanges or supply side platforms(SSPs). A RTB agent has a set of active ad campaigns each with…