考虑共现协作信号和对比学习的微信地图冷启动推荐方法

IF 1 4区地球科学 Q4 GEOGRAPHY, PHYSICAL

Journal of Spatial Science Pub Date : 2024-03-15 DOI:10.1080/14498596.2024.2325344

Wenjun Ma, Haowen Yan, Jingzhong Li, Xiaolong Wang, Zhuo Wang, Qili Yang, Xuan Fu

引用次数: 0

摘要

作为传统地图的补充，We-map 面临着现有推荐技术的冷启动问题。对比协作过滤（CCF）模型解决了We-map的冷启动问题 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A cold-start recommendation method for We-map considering co-occurrence collaborative signals and contrastive learning

We-maps, augmenting traditional maps, confront cold-start problems with prevailing recommendation techniques. The Contrastive Collaborative Filtering (CCF) model tackles We-map's cold-start issues ...

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来源期刊

Journal of Spatial Science 地学-地质学

CiteScore

5.00

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal of Spatial Science publishes papers broadly across the spatial sciences including such areas as cartography, geodesy, geographic information science, hydrography, digital image analysis and photogrammetry, remote sensing, surveying and related areas. Two types of papers are published by he journal: Research Papers and Professional Papers. Research Papers (including reviews) are peer-reviewed and must meet a minimum standard of making a contribution to the knowledge base of an area of the spatial sciences. This can be achieved through the empirical or theoretical contribution to knowledge that produces significant new outcomes. It is anticipated that Professional Papers will be written by industry practitioners. Professional Papers describe innovative aspects of professional practise and applications that advance the development of the spatial industry.