A personalized tourism recommendation method and system based on user behavior tags
By extracting visual embedded tags from user behavior and combining them with multilayer perceptrons for access prediction, this method solves the problem of neglecting unstructured visual information in existing recommendation methods, and achieves personalized and accurate travel recommendations.
CN122412686APending Publication Date: 2026-07-17SONGCHENG DUMUQIAO NETWORK CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SONGCHENG DUMUQIAO NETWORK CO LTD
- Filing Date
- 2026-03-10
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing travel recommendation methods rely too heavily on structured data and text tags, failing to fully explore unstructured visual information in user behavior, resulting in insufficient recommendation accuracy.
Method used
By acquiring user behavior data, extracting preference image sets and generating visual embedding labels, and combining them with a pre-trained multilayer perceptron for access prediction, personalized tourist attraction recommendations are made.
Benefits of technology
It improves the personalization and accuracy of recommendations, dynamically adapts to changes in user interests, and provides richer and more personalized travel options.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122412686A_ABST
Abstract
本发明公开了一种基于用户行为标签的个性化旅游推荐方法及系统，涉及信息推荐技术领域。通过获取目标用户的行为数据，确定其偏好图像集，并提取视觉信息生成偏好嵌入标签；根据用户查询信息确定候选景点集合，再通过景点展示图像提取视觉信息生成景点视觉嵌入标签；将偏好嵌入标签与景点视觉嵌入标签输入预训练的多层感知机进行访问预测，得到用户对各候选景点的访问概率；按访问概率降序输出推荐结果。本发明通过提取用户隐性审美偏好并精准匹配景点视觉特征，突破了文字标签模糊性，提升了推荐的个性化和精准度，为用户提供更加丰富的旅游推荐。
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Citation Information
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