行为挖掘、生成式对话与协同咨询：旅游推荐系统的未来
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自电子商务早期应用以来，旅游业一直是推荐系统设计的试验场：这类工具帮助旅行者选择目的地、航班、住宿，并将其组合成行程。数据驱动的推荐技术，从基于案例的推理到强化学习，已适应旅行者的需求。研究界已开发出多样化的旅游推荐系统（TTRSs）原型，这些系统依赖于情境，……
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Behavior-Mining, Generative Conversations, and Collaborative Advisory: the Future of Travel and Tourism Recommender Systems
Since the early adoption of e-commerce, travel and tourism has been a lab for the design of recommender systems: tools that help travelers choose destinations, flights, accommodations, and combine them into itineraries. Data-driven recommendation techniques, ranging from case-based reasoning to reinforcement learning, have been adapted to travelers' needs. The research community has produced multifaceted prototypes of travel and tourism recommender systems (TTRSs), which are context-dependent, m…
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相关来源
- 01arXiv · AI 文旅预印本原文
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