Title :
Search-Based Advertising Auctions With Choice-Based Budget Constraint
Author :
Tsan-Ming Choi ; Xun Li ; Cheng Ma
Author_Institution :
Inst. of Textiles & Clothing, Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
In this paper, we model and formulate the search-based advertising auction problem with multiple slots, choice behaviors of advertisers, and the popular generalized second-price mechanism. A Lagrangian-based method is then proposed for tackling this problem. We present an extension to the subgradient algorithm based on Lagrangian relaxation coupled with the column generation method in order to improve the dual multipliers and accelerate its convergence. Simulation results show that the proposed algorithm is efficient and it shows significant improvement compared to the greedy algorithm.
Keywords :
advertising data processing; commerce; convergence; relaxation; search engines; Lagrangian relaxation; choice-based budget constraint; column generation method; convergence; dual multipliers; popular generalized second-price mechanism; search-based advertising auction problem; subgradient algorithm; Advertising; Google; Linear programming; Optimization; Search engines; Search problems; Vectors; Generalized second-price (GSP) mechanism; online auction; search-based advertising (SA);
Journal_Title :
Systems, Man, and Cybernetics: Systems, IEEE Transactions on
DOI :
10.1109/TSMC.2015.2394501