Zobrazeno 1 - 10
of 5 302
pro vyhledávání: '"point of interest"'
Autor:
Junjun Zhi, Liangwei Ge, Tao Geng, Zhonghao Zhang, Lin Li, Hong Zhu, Zequn Zhou, Wei Jiang, Le’an Qu, Yue Su, Wangbing Liu
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1, Pp 1-26 (2024)
Both the physical features and social functions of urban green spaces (UGSs) are crucially important to the ecological and social benefits of urban residents. Increasing attention has been focused on exploring how UGS social functions affect the ecol
Externí odkaz:
https://doaj.org/article/ac1cc0e7716249a68895cf86a561e29f
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8163-8177 (2024)
Abstract With the continuous accumulation of massive amounts of mobile data, point-of-interest (POI) recommendation has become a vital task for location-based social networks. Deep neural networks or matrix factorization (MF) alone are challenging to
Externí odkaz:
https://doaj.org/article/6abf081c45bb478598ca663d785070a7
Publikováno v:
Geo-spatial Information Science, Pp 1-25 (2024)
Building use identification is crucial in urban planning and management. Current identification methods often rely on a single data source and neglect spatial proximity. In this paper, we propose a stepwise urban building use identification framework
Externí odkaz:
https://doaj.org/article/758125cb04bf494eb02e0dd08106fa42
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 7, Pp 1865-1878 (2024)
How to capture the dynamic changes and dependencies of user behavior is a vital issue existing in point-of-interest (POI) recommendation. It mainly faces challenges including data scarcity, difficulty in extracting spatio-temporal sequence features a
Externí odkaz:
https://doaj.org/article/1f7a70541a844647ab87b421ff6bd509
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 755-767 (2024)
The increasingly large scale of location-based social networks (LBSN) promotes the rapid development of point-of-interest (POI) recommendation business. POI geospatial distance directly adopted by traditional methods is difficult to simulate the high
Externí odkaz:
https://doaj.org/article/834a236111804c588f18f8a71e5465ff
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 2, Pp 384-397 (2024)
ABSTRACTNext point-of-interest (POI) recommendation has been applied by many internet companies to enhance the user travel experience. Recent research advocates deep-learning methods to model long-term check-in sequences and mine mobility patterns of
Externí odkaz:
https://doaj.org/article/3b9458f24e624ec7b320db08619b466e
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 2, Pp 505-522 (2024)
ABSTRACTIn recent years, decision support systems (DSSs) have successfully deployed ontologies in their architecture. The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities. V
Externí odkaz:
https://doaj.org/article/c088bd427e4f46e0b149f4d3c46609ea
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 2, Pp 455-474 (2024)
ABSTRACTPublic Map Service Platforms (PMSPs) provide embedded map services in domains such as forests and rivers. Users from different domains (Domain Users) prefer specific spatial features, and extracting the Browsing Interests of Domain Users (BID
Externí odkaz:
https://doaj.org/article/9b7cb0e975d849488cb8d80e52b80b46
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
Effectively identifying urban polycentric spatial structure (UPSS) is essential for data-driven evaluation of urban performance, and it serves as a scientific basis for urban spatial planning. However, existing identification methods have limitations
Externí odkaz:
https://doaj.org/article/fe2355463d2f47ceac47ee97427bd178
Publikováno v:
Frontiers in Sustainable Cities, Vol 6 (2024)
Externí odkaz:
https://doaj.org/article/0f1c732403e2460382c3147e8d7ff19e