E-resources
Peer reviewed
Open access
-
Liu, Mengjuan; Liu, Jinyu; Hu, Zhengning; Ge, Yuchen; Nie, Xuyun
Neurocomputing (Amsterdam), 08/2022, Volume: 501Journal Article
Real-time bidding (RTB) has become a critical way for online advertising. It allows advertisers to display their ads by bidding on ad impressions. Therefore, advertisers in RTB always seek an optimal bidding strategy to improve their cost-efficiency. Unfortunately, it is challenging to optimize the bidding strategy at the granularity of impression due to the highly dynamic nature of the RTB environment. In this paper, we focus on optimizing the single advertiser’s bidding strategy using a stochastic reinforcement learning (RL) algorithm. Firstly, we utilize a widely adopted linear bidding function to compute every impression’s base price and optimize it with a mutable adjustment factor, thus making the bidding price conform to not only the impression’s value to the advertiser but also the RTB environment. Secondly, we use the maximum entropy RL algorithm (Soft Actor-Critic) to optimize every impression’s adjustment factor to overcome the deterministic RL algorithm’s convergence problem. Finally, we evaluate the proposed strategy on a benchmark dataset (iPinYou), and the results demonstrate it obtained the most click numbers in 9 of 12 experiments compared to baselines.
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.