Design and Implementation of a Content Flow Control System for Xianyu Community
The Xianyu “Play” tab flow‑control system combines task‑specific and rule‑based strategies with a dynamic strategy‑, control‑, and distribution‑chain architecture that integrates real‑time data processing into the recommendation engine, delivering guaranteed exposure, boosting daily posts by 14.4 % and paving the way for multi‑objective, zero‑code control.
Background: In Xianyu's "Play" tab, a content community requires efficient matching between content and users, measured by CTR and dwell time. Operational needs include activity promotion, ecosystem balance, and flow support.
System Design: To avoid high development cost and conflicts with algorithm goals, a flow control system provides flexible traffic regulation, integrating with recommendation algorithms while meeting operational requirements.
Requirements are abstracted into two types: (1) task-specific flow control for particular content, time, scenario, and audience; (2) rule-based control that auto‑creates tasks when events (e.g., qualified creator publishes content) occur.
Implementation: A strategy chain dynamically creates control tasks, managed and scheduled by a control pipeline. The distribution chain connects to the recommendation system, optimizing core metrics.
Data Processing Service collects exposure logs in real time, updates task status, and stores data for insight analysis, using a high‑throughput low‑latency stream processing platform.
Strategy Chain: Normalizes heterogeneous events into standard strategy events, which are routed to StrategyManager and corresponding executors to generate control tasks.
Control Chain: After task generation, scheduling syncs tasks to a graph‑database‑backed control pool used by the recommendation engine. Real‑time logs trigger exposure/click metrics, update the pool, and finish tasks when targets are met.
Distribution Chain: During recall, the system merges controlled content with regular recall results for personalized matching. Ranking combines core metric models and specific control models, respecting operator priorities.
Summary & Outlook: The system currently supports guaranteed delivery and cold‑start strategies for key creators, achieving millions of exposures and a 14.4% increase in daily posts. Future work includes multi‑objective control (exposure, clicks, follower growth) and configurable, zero‑code strategy management.
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