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发表刊物：Big Earth Data

摘要：Without explicit description of map application themes, it is difficult for users to discover desired map resources from massive online Web Map Services (WMS). However, metadata-based map application theme extraction is a challenging multi-label text classification task due to limited training samples, mixed vocabularies, variable length and content arbitrariness of text fields. In this paper, we propose a novel multi-label text classification method, Text GCN-SW-KNN, based on geographic semantics and collaborative training to improve classification accuracy. The semi-supervised collaborative

论文类型：期刊论文

论文编号：10.1080/20964471.2021.1877434

文献类型：J

是否译文：否

发表时间：2021-02-24

发布期刊链接：https://www.tandfonline.com/doi/full/10.1080/20964471.2021.1877434