A personalized advertisement pushing method and system based on user portrait
By preprocessing data and analyzing link congestion constraints in the advertising push system, combined with interest-driven candidate compression and revenue-driven collaborative adjudication, the resource competition and latency issues of the advertising push system under high-concurrency requests are resolved, achieving more efficient and stable personalized advertising push.
Patent Information
- Application Number
- CN202610381298.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-26
- Publication Date
- 2026-06-23
AI Technical Summary
In high-concurrency request scenarios, existing advertising push systems suffer from resource contention and request queuing due to the shared computing resources for candidate ad feature extraction, prediction model invocation, and ranking decisions, which affects system response efficiency and push stability.
By collecting ad request data, user behavior log data, and push link operation data, and performing preprocessing, push link congestion constraint analysis is conducted. Combined with interest-driven candidate compression and ad revenue collaborative ad decision-making, the size of the candidate ad set is dynamically adjusted and the ranking decision is made to optimize the ad push process.
It effectively solves the problem of increased computing resource consumption caused by the expansion of candidate ad scale, improves the matching degree between ad push content and user interests, stabilizes the operation of the push link, and optimizes the benefits and display fairness of ad ranking decisions.
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Abstract
Citation Information
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