Intelligent Cloud Customer Service Platform: Overview, Architecture, and Key AI Models

In the era of artificial intelligence, AI technologies are transforming business models by improving process efficiency, communication, cost reduction, and revenue growth. Ctrip's intelligent cloud customer service platform exemplifies these advances, significantly enhancing service efficiency and user experience.

1. Platform Overview Before the platform’s launch, multiple service channels (IM/WeChat, online chat, phone) suffered from various pain points due to the diversity of products (hotels, flights, tickets). The platform targets six improvement areas: service flow efficiency, response time, standardization, automation, violation management, and process optimization. It now operates nearly 80 models across intelligent Q&A, channel management, process optimization, and vendor management.

2. System Architecture The architecture includes an algorithm layer with an auto‑correction model that raised user intent recognition accuracy from 60% to over 90%, and an engineering layer featuring the EasyAI platform, which enables non‑technical business users to improve work efficiency by 50%.

3. Typical Algorithm Models

• User Intent Model : A deep‑learning multi‑task, multi‑label model that detects purchase intent in real‑time to enable personalized recommendations.

• Group Supervision Model : Addresses extreme class imbalance in group‑based chat data, boosting accuracy from just over 10% to above 80%.

• Content Extraction Model : A semi‑supervised model that augments standard extraction techniques with a custom language model, improving accuracy by 7%.

• Knowledge Graph Construction : Involves domain segmentation, manual schema definition, information extraction, and subsequent graph completion, fusion, and reasoning.

• Self‑service QA Model : Evolved from version 1.0 (Bi‑LSTM + Attention + CNN coarse‑grained retrieval) to 2.0, which supports multi‑turn dialogue, automatic error correction, intent understanding, dialogue management, answer ranking, and recommendation.

4. EasyAI Platform Designed for business users, EasyAI streamlines data annotation, model training, and resource sharing, reducing development cycles and avoiding duplicate model construction.

Conclusion The intelligent cloud customer service platform demonstrates the broad value of AI for Ctrip, with future plans to extend knowledge graph applications to recommendation, search, and machine reading in the tourism domain, ultimately achieving full‑process automation and intelligence.