从非结构化中文文本中识别细粒度高速公路位置参考的深度学习方法

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-01-09 DOI:10.1080/13658816.2023.2301316

Qilong Wu, Peiwen Yao, Haihong Zhu, Wei Zhu, Yukun Wu, Lin Li

引用次数: 0

摘要

在非结构化文本中，复杂的嵌套和不连续的位置参考信息很常见。提取它们对于准确的位置信息检索和空间推理至关重要。然而，传统的位置信息检索方法并不能解决这个问题。

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 deep learning approach to recognizing fine-grained expressway location reference from unstructured texts in Chinese

Complex nested and discontinuous location references are common in unstructured text. Extracting them is essential for accurate location information retrieval and spatial inference. However, tradit...

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.