{"title":"从空间互动中学习地点表征","authors":"Xuechen Wang, Huanfa Chen, Yu Liu","doi":"10.1080/13658816.2024.2332908","DOIUrl":null,"url":null,"abstract":"The development of geospatial artificial intelligence (GeoAI) systems depends on the ability to learn effective representations of places. To learn accurate place representations from spatial inter...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"158 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Learning place representations from spatial interactions\",\"authors\":\"Xuechen Wang, Huanfa Chen, Yu Liu\",\"doi\":\"10.1080/13658816.2024.2332908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of geospatial artificial intelligence (GeoAI) systems depends on the ability to learn effective representations of places. To learn accurate place representations from spatial inter...\",\"PeriodicalId\":14162,\"journal\":{\"name\":\"International Journal of Geographical Information Science\",\"volume\":\"158 1\",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geographical Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/13658816.2024.2332908\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geographical Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/13658816.2024.2332908","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Learning place representations from spatial interactions
The development of geospatial artificial intelligence (GeoAI) systems depends on the ability to learn effective representations of places. To learn accurate place representations from spatial inter...
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.