Real-Time Bidding Benchmarking with iPinYou Dataset
Weinan Zhang, Shuai Yuan, Jun Wang, Xuehua Shen

TL;DR
This paper introduces the first publicly available dataset for real-time bidding in display advertising, enabling reproducible research and benchmarking in bid optimization and CTR estimation.
Contribution
It provides a comprehensive dataset from iPinYou, detailed statistical analysis, and benchmark experiments for bid optimization and CTR estimation in RTB.
Findings
Dataset enables reproducible RTB research
Benchmark results for CTR estimation accuracy
Benchmark results for bid optimization performance
Abstract
Being an emerging paradigm for display advertising, Real-Time Bidding (RTB) drives the focus of the bidding strategy from context to users' interest by computing a bid for each impression in real time. The data mining work and particularly the bidding strategy development becomes crucial in this performance-driven business. However, researchers in computational advertising area have been suffering from lack of publicly available benchmark datasets, which are essential to compare different algorithms and systems. Fortunately, a leading Chinese advertising technology company iPinYou decided to release the dataset used in its global RTB algorithm competition in 2013. The dataset includes logs of ad auctions, bids, impressions, clicks, and final conversions. These logs reflect the market environment as well as form a complete path of users' responses from advertisers' perspective. This…
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Taxonomy
TopicsVehicle License Plate Recognition · Smart Parking Systems Research · Video Analysis and Summarization
