MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search
Miao Fan, Jiacheng Guo, Shuai Zhu, Shuo Miao, Mingming Sun, Ping Li

TL;DR
This paper introduces MOBIUS, a next-generation query-ad matching system for Baidu's sponsored search, which jointly optimizes relevance and business metrics like CPM by training a neural CTR predictor and employing advanced retrieval techniques.
Contribution
It presents a novel approach to integrate CPM optimization into the matching layer and employs active learning and SOTA ANN search for efficiency and effectiveness.
Findings
Improved ad matching relevance and business performance.
Effective use of active learning for training neural click models.
Enhanced ad retrieval efficiency with advanced ANN techniques.
Abstract
Baidu runs the largest commercial web search engine in China, serving hundreds of millions of online users every day in response to a great variety of queries. In order to build a high-efficiency sponsored search engine, we used to adopt a three-layer funnel-shaped structure to screen and sort hundreds of ads from billions of ad candidates subject to the requirement of low response latency and the restraints of computing resources. Given a user query, the top matching layer is responsible for providing semantically relevant ad candidates to the next layer, while the ranking layer at the bottom concerns more about business indicators (e.g., CPM, ROI, etc.) of those ads. The clear separation between the matching and ranking objectives results in a lower commercial return. The Mobius project has been established to address this serious issue. It is our first attempt to train the matching…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Management and Algorithms · Web Data Mining and Analysis · Advanced Database Systems and Queries
