Document Type
Thesis
Date of Award
5-31-2023
Degree Name
Master of Science in Data Science - (M.S.)
Department
Computer Science
First Advisor
Pan Xu
Second Advisor
Zuofeng Shang
Third Advisor
James Geller
Abstract
One of the classical problems in graph theory is matching. Given an undirected graph, find a matching which is a set of edges without common vertices. In 1990s, Richard Karp, Umesh Vazirani, and Vijay Vazirani would be the first computer scientists to use matchings for online algorithms [8]. In our domain, an online algorithm operates in the online setting where a bipartite graph is given. On one side of the graph there is a set of advertisers and on the other side we have a set of impressions. During the online phase, multiple impressions will arrive and the objective of the online algorithm is to match incoming impressions to advertisers. The theory behind online matching is not only fascinating but has a lot of practical applications. One example is ridesharing platforms like Uber. An online algorithm can be used to assign incoming requests to available Uber drivers in order to maximize profits and fairness.
Recommended Citation
Lee, Ryan, "A survey on online matching and ad allocation" (2023). Theses. 2186.
https://digitalcommons.njit.edu/theses/2186
Included in
Data Science Commons, Discrete Mathematics and Combinatorics Commons, Statistics and Probability Commons, Theory and Algorithms Commons
