Multi‐Row Labeling With Semantic Analysis: A Case Study on Chinese POIs

• DOI: 10.1111/tgis.70024
• Publication Date: 2025-03-27T02:13:20Z
• Authors: Zhiwei Wei; Junguo Shi; Nai Yang; Yunfei Zhang; Wenjia Xu; Su Ding; Minmin Li; Renzhong Guo

ABSTRACT Labels are widely used in maps to convey verbal information for symbols and play a crucial role aiding users' navigation understanding of spatial context. Traditional labeling approaches mainly focus on ensuring label readability by placing them overlap‐free while maintaining visual coherence. However, these methods often fall short Point Interest (POI) labeling, particularly the context Chinese labels, due growing demand detailed informative with long or descriptive POI names. To address this challenge, it is essential shorten names split labels into multiple rows achieve more effective layout. In work, we present multi‐row algorithm that introduces new quality constraints incorporates linguistic semantic analysis preprocessing, segmentation, placement. We also demonstrate its application real‐world mapping platform, Meituan Map, which serves over 50 million monthly users. inform design algorithm, interviewed six domain experts conducted statistical based dataset containing 160,297 POIs. This confirms necessity highlights practical challenges considerations. Our results indicate preprocessing phase our can reduce total character count 41.15% word 43.24%. Comparative experiments show approach achieves superior placement terms clarity. improvement may come at cost increased computational time. A user study involving 318 participants demonstrated processing result user‐preferred layout comparable effectiveness tasks, although increase response