Ads Searching System Description

  • Project Overview

    Ads Searching is a multi-billion dollar business. In this project, we will implement a simplified search ads stack which selects ads for a given query and returns sorted ads based on some ranking criteria.

    Basic process flow: Query understanding -> Select Ads Candidates -> Rank Ads ->Filter Ads -> Pricing -> Allocate Ads

    *This is an open-ended challenge. Do your best to come up with your own implementation

    Project Description


    First stage: Build query understanding module using a basic Natural Language Processing algorithm[1]: query cleaning, tokenize.
    Second stage: Build an index for Ads Data including an inverted index[2] and a forward index[3]. We may use a key value store such as memcached.
    Schema of reverted index – Key: word, Value: list
    Schema of forward index
    Third stage: Implement Ads selection and rank logic
    Suggested Prerequisite Knowledge
    Basic Java
    Basic knowledge of key value storage[3]
    Submission Instructions
    Please upload your final code to your Github account
    Please record a video explaining the design choices you made including: the overall structure of the application, how you chose to index and retrieve ads, and any other features you would like to highlight. Please keep the video under 5 minutes.


    [2]Inverted Index:
    [3]Key Value Storage:


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