全球位置信息叠加协议与位置服务网技术研究进展与展望

doi:10.12082/dqxxkx.2022.210762

Abstract

Abstract:

With the rapid development of information technology, the world has entered an era of explosive growth of information, the Internet, the Internet of Things, and sensor networks have flooded with massive amounts of human society related information, providing us with a new way to solve urban governance and social management issues. The biggest challenge to further improve the ability of urban smart management is that information cannot be integrated and shared quickly and effectively. Therefore, the global location information superposition protocol and location-based service network technology have been proposed, based on the location-based fact of most social information, which become a key technology to break the barriers between systems in various fields, and to make the automatic collection, integration of computing, and intelligent services of massive heterogeneous information across networks, platforms, systems, and languages come true. This paper summarizes the current domestic and foreign research progress on the key technologies of the global location information superposition protocol and location-based service network, and then introduces the demonstration application of the global location-based service network. Finally, the technology and application of the global location-based service network on the future research directions are discussed, which can be the reference for the development of the global location-based service network in the future.

Key words: location service network, location code, location information superposition protocol, spatial-temporal information fusion, collaborative computing

GONG Jianya, HUANG Wenzhe, CHEN Zeqiang, LIU Yuting, LI Lin, TANG Weiming, ZHANG Qianli, CHEN Jing, CHEN Bo, YUE Peng, LIU Jun, XIAO Jihua. Global Location Information Superposition Protocol and Location-based Service Network Technology: Progress and Prospects[J].Journal of Geo-information Science, 2022, 24(1): 2-16.DOI:10.12082/dqxxkx.2022.210762

Figures/Tables 7

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References 95

[1]	李清泉, 李德仁. 大数据GIS[J]. 武汉大学学报(信息科学版), 2014, 39(6):641-644,666.
	[ Li Q Q, L D R. Big data GIS[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6):641-644,666. ] DOI: 10.13203/j.whugis20140150 doi: 10.13203/j.whugis20140150
[2]	李德仁. 脑认知与空间认知——论空间大数据与人工智能的集成[J]. 武汉大学学报(信息科学版), 2018, 43(12):1761-1767.
	[ Li D R. Brain cognition and spatial cognition:on integration of Geo-spatial big data and artificial intelligence[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):1761-1767. ] DOI: 10.13203/j.whugis20180411 doi: 10.13203/j.whugis20180411
[3]	龚健雅, 郝哲. 信息化时代新型测绘地理信息技术的发展[J]. 中国测绘, 2019(7):25-30.
	[ Gong J Y, Hao L. Development of new surveying and mapping geographic information technology in the information age[J]. China Surveying and Mapping, 2019(7):25-30. ] DOI: CNKI:SUN:ZCHZ.0.2019-07-005 doi: CNKI:SUN:ZCHZ.0.2019-07-005
[4]	程承旗. 空间信息剖分组织导论[M]. 北京: 科学出版社, 2012.
	[ Cheng C Q. Introduction to spatial information dissection organization[M]. Beijing: Science Press, 2012. ]
[5]	兀伟, 邓国庆, 程承旗, 等. 国家标准《地球空间网格编码规则》编制说明[J]. 测绘标准化, 2021, 37(3):5-10.
	[ Wu W, Deng G Q, Cheng C Q, et al. Description for national standard geospatial grid encoding rule[J]. Standardization of Surveying and Mapping, 2021, 37(3):5-10. ]
[6]	程承旗, 付晨. 地球空间参考网格及应用前景[J]. 地理信息世界, 2014, 21(3):1-8.
	[ Cheng C Q, Fu C. Earth space reference grid and its application prospect[J]. Geomatics World, 2014, 21(3):1-8. ] DOI: 10.3969/j.issn.1672-1586.2014.03.001 doi: 10.3969/j.issn.1672-1586.2014.03.001
[7]	李德仁, 崔巍. 地理本体与空间信息多级网格[J]. 测绘学报, 2006, 35(2):143-148.
	[ Li D R, Cui W. Geographic Ontology and SIMG[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(2):143-148. ] DOI: 10.3321/j.issn:1001-1595.2006.02.010 doi: 10.3321/j.issn:1001-1595.2006.02.010
[8]	宁津生, 王正涛. 测绘学科发展综述[J]. 测绘科学, 2006, 31(1):9-16,3.
	[ Ning J S, Wang Z T. Review on the development of surveying and mapping[J]. Science of Surveying and Mapping, 2006, 31(1):9-16,3. ] DOI: 10.3771/j.issn.1009-2307.2006.01.001 doi: 10.3771/j.issn.1009-2307.2006.01.001
[9]	杨元喜, 李金龙, 王爱兵, 等. 北斗区域卫星导航系统基本导航定位性能初步评估[J]. 中国科学:地球科学, 2014, 44(1):72-81.
	[ Yang Y X, Li J L, Wang A B, et al. Preliminary evaluation of the basic navigation and positioning performance of Beidou regional satellite navigation system[J]. Scientia Sinica(Terrae), 2014, 44(1):72-81. ] DOI: 10.1360/zd-2014-44-1-72 doi: 10.1360/zd-2014-44-1-72
[10]	沈钲晨, 张千里, 张沛, 等. 基于地理位置的IPv6地址生成方式研究与设计[C]. 2018中国信息通信大会(CICC 2018), 2018.
	[ Shen Z C, Zhang Q L, Zhang P, et al. Research and Design of IPv6 Address Generation Method Based on Geographical Location[C]. 2018 China Information and Communication Conference(CICC 2018), 2018]
[11]	张千里, 姜彩萍, 王继龙, 等. IPv6地址结构标准化研究综述[J]. 计算机学报, 2019, 42(6):1384-1405.
	[ Zhang Q L, Jiang C P, Wang J L, et al. A survey on IPv6 address structure standardization researches[J]. Chinese Journal of Computers, 2019, 42(6):1384-1405. ] DOI: 10.11897/SP.J.1016.2019.01384 doi: 10.11897/SP.J.1016.2019.01384
[12]	自然资源部(测绘地理). 20210654-T-466,泛在位置信息叠加协议[S]. 全国地理信息标准化技术委员会, 2021.
	[ Ministry of Natural Resources (Surveying and Mapping Geography). 20210654-T-466, Protocol for Information Superposition based on Ubiquitous Location[S]. National Geographic Information Standardization Technical Committee, 2021. ]
[13]	吴信才. 地理信息系统的基本技术与发展动态[J]. 地球科学, 1998, 23(4):5-9.
	[ Wu X C. Basic technology and development of geographic information system[J]. Earth Science, 1998, 23(4):5-9. ] DOI: 10.3321/j.issn:1000-2383.1998.04.001 doi: 10.3321/j.issn:1000-2383.1998.04.001
[14]	Fotheringham S, Rogerson P. Spatial analysis and GIS[M]. CRC Press, 2013.
[15]	Dow J M, Neilan R E, Rizos C. The international GNSS service in a changing landscape of global navigation satellite systems[J]. Journal of geodesy, 2009, 83(3):191-198. DOI: 10.1007/s00190-008-0300-3 doi: 10.1007/s00190-008-0300-3
[16]	宁津生, 姚宜斌, 张小红. 全球导航卫星系统发展综述[J]. 导航定位学报, 2013, 1(1):3-8.
	[ Ning J S, Yao Y B, Zhang X H. Review of the Development of Global Satellite Navigation System[J]. Journal of Navigation and Positioning, 2013, 1(1):3-8. ] DOI: 10.16547/j.cnki.10-1096.2013.01.005 doi: 10.16547/j.cnki.10-1096.2013.01.005
[17]	Zou X, Wang Y, Deng C, et al. Instantaneous BDS+GPS undifferenced NRTK positioning with dynamic atmospheric constraints[J]. GPS Solutions, 2018, 22(1):17. DOI: 10.1007%2Fs10291-017-0668-8 doi: 10.1007%2Fs10291-017-0668-8
[18]	Li X, Ge M, Dai X, et al. Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo[J]. Journal of Geodesy, 2015, 89(6):607-635. DOI: 10.1007/s00190-015-0802-8 doi: 10.1007/s00190-015-0802-8
[19]	李德仁, 王密, 沈欣, 等. 从对地观测卫星到对地观测脑[J]. 武汉大学学报·信息科学版, 2017, 42(2):143-149.
	[ Li D R, Wang M, Shen X, et al. From earth observation satellite to earth observation brain[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2):143-149. ] DOI: 10.13203/j.whugis20160526 doi: 10.13203/j.whugis20160526
[20]	李德仁. 新基建时代地理信息产业的机遇与挑战[J]. 中国工业和信息化, 2020, 12:52-57.
	[ Li D R. Opportunities and challenges of geographic information industry in the era of new infrastructure[J]. China Industry & Information Technology, 2020,(12):52-57. ] DOI: 10.19609/j.cnki.cn10-1299/f.2020.12.008 doi: 10.19609/j.cnki.cn10-1299/f.2020.12.008
[21]	李德仁. 展望5G/6G时代的地球空间信息技术[J]. 测绘学报, 2019, 48(12):1475-1481.
	[ Li D R. Towards geospatial information technology in 5g/6g Era[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12):1475-1481. ] DOI: 10.11947/j.AGCS.2019.20190437 doi: 10.11947/j.AGCS.2019.20190437
[22]	刘艳红, 黄雪涛, 石博涵. 中国“新基建”:概念、现状与问题[J]. 北京工业大学学报(社会科学版), 2020, 20(6):1-12.
	[ Liu Y H, Huang X T, Shi B B. China's new infrastructure construction: Concepts, current situations and problems[J]. 2020, 20(6):1-12. ] DOI: 10.3771/j.issn.1009-2307.2006.01.001 doi: 10.3771/j.issn.1009-2307.2006.01.001
[23]	尤肖虎, 潘志文, 高西奇, 等. 5G移动通信发展趋势与若干关键技术[J]. 中国科学:信息科学, 2014, 44(5):551-563.
	[ You X H, Pan Z W, Gao X Q, et al. The 5g mobile communication: the development trends and its emerging key techniques[J]. Scientia Sinica(Informationis), 2014, 44(5):551-563. ] DOI: 10.1360/N112014-00032 doi: 10.1360/N112014-00032
[24]	罗军舟, 吴文甲, 杨明. 移动互联网:终端、网络与服务[J]. 计算机学报, 2011, 34(11):2029-2051.
	[ Luo J Z, Wu W J, Yang M. Mobile internet: Terminal devices, networks and services[J]. Chinese Journal of Computers, 2011, 34(11):2029-2051. ] DOI: 10.3724/SP.J.1016.2011.02029 doi: 10.3724/SP.J.1016.2011.02029
[25]	龚健雅. 当代地理信息系统进展综述[J]. 测绘与空间地理信息, 2004, 27(1):5-11.
	[ Gong J Y. Review of the progress in contemporary GIS[J]. Geomatics & Spatial Information Technology, 2004, 27(1):5-11. ] DOI: 10.3969/j.issn.1672-5867.2004.01.001 doi: 10.3969/j.issn.1672-5867.2004.01.001
[26]	漆锟, 程承旗, 陈波. 北斗导航网格码在空天信息组织中的应用[C]. 2016年航空科学与技术全国博士生学术论坛, 2016: 48.
	[ Qi K, Cheng C Q, Chen B. Application of beidou navigation Grid code in aerospace information organization[C]. 2016 National Academic Forum for Doctoral Students in Aviation Science and Technology, 2016: 48. ]
[27]	李潇. 北斗网格码:一码标记全球[N]. 学习时报, 2021-11-24(006).
	[ Li X. Beidou grid code: Mark the world with one code[N]. Study times, 2021-11-24(006). ]
[28]	李林, 程承旗, 任伏虎. 北斗网格码:数字孪生城市CIM时空网格框架[J]. 信息通信技术与政策, 2021(11):1-5.
	[ Li L, Cheng C Q, Ren F H. Beidou grid code: Cim spatio-temporal grid framework for digital twin cities[J]. Information and Communications Technology and Policy, 2021(11):1-5. ] DOI: 10.12267/j.issn.2096-5931.2021.11.001 doi: 10.12267/j.issn.2096-5931.2021.11.001
[29]	中国军委装备发展部. GJB 8896-2017,地球表面空间网格与编码[S]. 全国地理信息标准化技术委员会, 2017.
	[ Equipment Development Department of the Chinese Military Commission. GJB 8896-2017, Earth surface space grid and coding[S]. National Geographic Information Standardization Technical Committee, 2017. ]
[30]	自然资源部(测绘地理). GB/T 40087-2021,地球空间网格编码规则[S]. 全国地理信息标准化技术委员会, 2021.
	[ Ministry of Natural Resources (Surveying and Mapping Geography). GB/T 40087-2021, Geospatial grid coding rules[S]. National Geographic Information Standardization Technical Committee, 2021. ]
[31]	中央军委装备发展部. GB/T 39409-2020,北斗网格位置码[S]. 全国北斗卫星导航标准化技术委员会, 2020.
	[ Central Military Commission Equipment Development Department. GB/T 39409-2020, Beidou grid location code[S]. National Beidou Satellite Navigation Standardization Technical Committee, 2020. ]
[32]	魏小峰, 程承旗, 陈波, 等. 基于独立边数的链码方法[J]. 浙江大学学报, 2018, 52(9):61-68.
	[ Wei X F, Cheng C Q, Chen B, et al. Chain code based on independent edge number[J]. Journal of Zhejiang University, 2018, 52(9):61-68. ] DOI: 10.3785/j.issn.1008-973X.2018.09.008 doi: 10.3785/j.issn.1008-973X.2018.09.008
[33]	魏小峰, 程承旗, 陈波, 等. 利用不规则线段组合的压缩链码[J]. 计算机辅助设计与图形学学报, 2018, 30(10):54-61.
	[ Wei X F, Cheng C Q, Chen B, et al. A compressed Chain code based on irregular line segments combination[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(10):54-61. ] DOI: CNKI:SUN:JSJF.0.2018-10-007 doi: CNKI:SUN:JSJF.0.2018-10-007
[34]	Maxmind.GeoIP2 City Accuracy[DB/OL]. https://www.maxmind.com/en/geoip2-city-accuracy-comparison?country=&resolution=50&cellular=all.
[35]	Hain.An IPv6 Geographic Global Unicast Address Format[DB.OL].https://datatracker.ietf.org/doc/draft- hain- ipv6- geoaddr/.
[36]	新华三技术有限公司. IPv6组播地址的生成方法和装置[P]. 发明专利,CN201910939895.8. 2019-09-30.
	[ New H3C Technology Co., Ltd.. Method and device for generating IPv6 multicast address[P]. Patent, CN201910939895.8. 2019-09-30.
[37]	沈钲晨, 张千里, 张超凡, 等. 基于深度学习的位置隐私攻击[J]. 计算机研究与发展, 2021,1-14.
	[ Shen Z C, Zhang Q L, Zhang C F, et al. Location privacy attack based on deep learning[J]. Journal of Computer Research and Development, 2021,1-14. ]
[38]	Dong Q, Chen J, Liu T. A topographically preserved road-network tile model and optimal routing method for virtual globes[J]. Transactions in GIS, 2019, 23(2):294-311. DOI: 10.1111/tgis.12520 doi: 10.1111/tgis.12520
[39]	自然资源部(测绘地理). GB/T 37118-2018,地理实体空间数据规范[S]. 全国地理信息标准化技术委员会, 2018.
	[ Ministry of Natural Resources (Surveying and Mapping Geography). GB/T 37118-2018, Geographic entity spatial data specification[S]. National Geographic Information Standardization Technical Committee, 2018. ]
[40]	国务院. 《国务院关于全国基础测绘中长期规划纲要(2015-2030年)的批复》[EB/OL]. 中华人民共和国中央人民政府, 2015-06-01: http://www.gov.cn/zhengce/content/2015-06/06/content_9830.htm.
	[ State Council, "Approval of the State Council on the National Basic Surveying and Mapping Medium and Long-term Planning Outline (2015-2030)" [EB/OL]. The Central People's Government of the People's Republic of China, 2015-06-01: http://www.gov.cn/zhengce/content/2015-06/06/content_9830.htm].
[41]	闾国年, 俞肇元, 周良辰, 等. 地理实体分类与编码体系的构建[J]. 现代测绘, 2019, 42(1):1-6.
	[ Lv G N, Yu Z Y, Zhou L C, et al. Construction of geographical entity classification and coding system[J]. Modern Surveying and Mapping, 2019, 42(1):1-6. ] DOI: CNKI:SUN:JSCH.0.2019-01-001 doi: CNKI:SUN:JSCH.0.2019-01-001
[42]	李成名, 印洁, 刘晓丽, 等. “实体中国”与新型基础测绘的思考[J]. 测绘科学, 2019, 44(6):230-234.
	[ Li C M, Yin J, Liu X L, et al. Thinking on the Feature China and new fundamental surveying and mapping[J]. Science of Surveying and Mapping, 2019, 44(6):230-234. ] DOI: 10.16251/j.cnki.1009-2307.2019.06.034 doi: 10.16251/j.cnki.1009-2307.2019.06.034
[43]	张红辉, 赵仁亮, 周晓光. 基于开源方式的多源网络地名数据库整合[J]. 地理信息世界, 2014, 21(1):22-28.
	[ Zhang H H, Zhao R L, Zhou X G. A method for integration of multi-source network geographic name data based on open source approach[J]. Geomatics World, 2014, 21(1):22-28. ] DOI: 10.3969/j.issn.1672-1586.2014.01.021 doi: 10.3969/j.issn.1672-1586.2014.01.021
[44]	Purves R S, Clough P, Jones C B, et al. The design and implementation of SPIRIT: A spatially aware search engine for information retrieval on the Internet[J]. International Journal of Geographical Information Science, 2007, 21(7):717-745. DOI: 10.1080/13658810601169840 doi: 10.1080/13658810601169840
[45]	黄恒琪, 于娟, 廖晓, 等. 知识图谱研究综述[J]. 计算机系统应用, 2019, 28(6):1-12.
	[ Huang H Q, Yu J, Liao X, et al. Review on knowledge graphs[J]. Computer Systems & Applications, 2019, 28(6):1-12. ] DOI: 10.15888/j.cnki.csa.006915 doi: 10.15888/j.cnki.csa.006915
[46]	Wang S, Zhang X, Ye P, et al. Geographic knowledge graph (GeoKG): A formalized geographic knowledge representation[J]. ISPRS International Journal of Geo-information, 2019, 8(4):184. DOI: 10.3390/ijgi8040184 doi: 10.3390/ijgi8040184
[47]	Qiu P, Gao J, Yu L, et al. Knowledge embedding with geospatial distance restriction for geographic knowledge graph completion[J]. ISPRS International Journal of Geo-Information, 2019, 8(6):254. DOI: 10.3390/ijgi8060254 doi: 10.3390/ijgi8060254
[48]	Nakamura E F, Loureiro A A, Frery A C, Information fusion for wireless sensor networks: Methods, models, and classifications[J]. ACM Computing Surveys, 2007, 39(3):9-es. DOI: 10.1145/1267070.1267073 doi: 10.1145/1267070.1267073
[49]	Beeri C, Kanza Y, Safra E, et al. Object fusion in geographic information systems[C]. Proceedings of the Thirtieth international conference on Very large data bases-Volume 30, 2004:816-827. DOI: 10.1016/B978-012088469-8/50072-3 doi: 10.1016/B978-012088469-8/50072-3
[50]	Zhang H, Li L, Hu W, et al. Visualization of location-referenced Web textual information based on map mashups[J]. IEEE Access, 2019, 7:40475-40487. DOI: 10.1109/ACCESS.2019.2907570 doi: 10.1109/ACCESS.2019.2907570
[51]	杨元喜, 任夏. 超高精度定位[J]. 中国科学基金, 2021, 35(3):410-412.
	[ Yang Y X, Ren X. Ultra-high precision positioning[J]. Bulletin of National Natural Science Foundation of China, 2021, 35(3):410-412. ] DOI: 10.16262/j.cnki.1000-8217.2021.03.018 doi: 10.16262/j.cnki.1000-8217.2021.03.018
[52]	梁益丰, 许江宁, 吴苗, 等. 高精度授时技术发展现状分析[J]. 现代导航, 2018, 9(5):331-334.
	[ Liang Y F, Xu J N, Wu M, et al. Analysis of development of high-precision time service technology[J]. Modern Navigation, 2018, 9(5):331-334. ] DOI: 10.3969/j.issn.1674-7976.2018.05.005 doi: 10.3969/j.issn.1674-7976.2018.05.005
[53]	Cui J, Yan R, Deng C, et al. GPS+BDS network real-time differential positioning using a position domain estimation method[J]. Remote Sensing, 2019, 11(12):1480. DOI: doi.org/10.3390/rs11121480 doi: doi.org/10.3390/rs11121480
[54]	Tang W, Shen M, Deng C, et al. Network-based triple-frequency carrier phase ambiguity resolution between reference stations using BDS data for long baselines[J]. GPS Solutions, 2018, 22(3):1-10. DOI: 10.1007/s10291-018-0737-7 doi: 10.1007/s10291-018-0737-7
[55]	余丽, 陆锋, 张恒才. 网络文本蕴涵地理信息抽取:研究进展与展望[J]. 地球信息科学学报, 2015, 17(2):127-134. doi: 10.3724/SP.J.1047.2015.00127
	[ Yu L, Lu F, Zhang H C. Extracting geographic information from Web texts: Status and development[J]. Journal of Geo-information Science, 2015, 17(2):127-134. ] DOI: 10.3724/SP.J.1047.2015.00127 doi: 10.3724/SP.J.1047.2015.00127
[56]	张雪英, 闾国年, 李伯秋, 等. 基于规则的中文地址要素解析方法[J]. 地球信息科学学报, 2010, 12(1):13-20.
	[ Zhang X Y, Lv G N, Li B Q. Rule based approach to semantic resolution of Chinese addresses[J]. Journal of Geo-information Science, 2010, 12(1):13-20. ] DOI: 10.3724/SP.J.1047.2010.00009 doi: 10.3724/SP.J.1047.2010.00009
[57]	王克永, 刘纪平, 罗安, 等. 前后缀与特征词相结合的地名地址提取[J]. 测绘通报, 2016, 2:64-68.
	[ Wang K Y, Liu J P, Luo A, et al. Extracting Toponomy and Location Based on the Combination of Prefix and Suffix with Feature Words[J]. Bulletin of Surveying and Mapping, 2016, 2:64-68. ] DOI: 10.13474/j.cnki.11-2246.2016.0050 doi: 10.13474/j.cnki.11-2246.2016.0050
[58]	俞鸿魁, 张华平, 刘群, 等. 基于层叠隐马尔可夫模型的中文命名实体识别[J]. 通信学报, 2006, 27(2):87-93.
	[ Yu H K, Zhang H P, Liu Q, et al. Chinese named entity identification using cascaded hidden Markov model[J]. Journal on Communications, 2006, 27(2):87-93. ] DOI: 10.3321/j.issn:1000-436X.2006.02.013 doi: 10.3321/j.issn:1000-436X.2006.02.013
[59]	李丽双, 黄德根, 陈春荣, 等. 基于支持向量机的中文文本中地名识别[J]. 大连理工大学学报, 2007, 47(3):126-131.
	[ Li L S, Huang D G, Chen C R, et al. Identification of location names from Chinese texts based on support vector machine[J]. Journal of Dalian University of Technology, 2007, 47(3):126-131. ] DOI: 10.3321/j.issn:1000-8608. 2007.03.025 doi: 10.3321/j.issn:1000-8608. 2007.03.025
[60]	邬伦, 刘磊, 李浩然, 等. 基于条件随机场的中文地名识别方法[J]. 武汉大学学报·信息科学版, 2017, 42(2):150-156.
	[ Wu L, Liu L, Li H R, et al. A Chinese toponym recognition method based on conditional random field[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2):150-156. ] DOI: 10.13203/j.whugis20141009 doi: 10.13203/j.whugis20141009
[61]	袁小芳. 基于CRF的城市火灾微博文本地名地址识别与精化处理方法[D]. 江西:江西师范大学, 2020.
	[ Yuan X F. CRF-based recognition and refined processing method of city fire microblog text place names and addresses[D]. JiangXi: Jiangxi Normal University, 2020. ]
[62]	沈思, 朱丹浩. 基于深度学习的中文地名识别研究[J]. 北京理工大学学报, 2017, 37(11):54-59.
	[ Shen S, Zhu D H. Chinese place name recognition based on deep learning[J]. Journal of Beijing Institute of Technology, 2017, 37(11):54-59. ] DOI: 10.15918/j.tbit1001-0645.2017.11.08 doi: 10.15918/j.tbit1001-0645.2017.11.08
[63]	邓中亮, 邱德武, 管孟, 等. 一种从文本信息中确定位置信息的方法[P]. 发明专利,201910554771.8. 2019-06-25.
	[ Deng Z L, Qiu D W, Guan M, et al. A method for determining location information from text information[P]. Patent, 201910554771.8. 2019-06-25.]
[64]	李霖, 罗振威, 朱海红, 等. 一种面向文本的相对位置信息提取方法[P]. 发明专利,202110479288.5. 2021-04-30.
	[ Li L, Luo Z W, Zhu H H, et al. A text-oriented method for extracting relative position information[P]. Patent, 202110 479288.5. 2021-04-30.]
[65]	Batista D S, Silva M J, Couto F M, et al. Geographic signatures for semantic retrieval[C]. Workshop on Geographic Information Retrieval, 2010:18-19.DOI: 10.1145/1722080.1722104 doi: 10.1145/1722080.1722104
[66]	蒙文清, 尹章才. 基于地名互现的城市联系强度研究——以湖北省为例[J]. 测绘地理信息, 2020, 45(2):31-34.
	[ Meng W Q, Yin Z C. A study on the strength of urban connection based on toponym Co-occurrences:A case study of Hube iProvince[J]. Journal of Geomatics, 2020, 45(2):31-34. ] DOI: 10.14188/j.2095-6045.2018268 doi: 10.14188/j.2095-6045.2018268
[67]	Santos J, Anastácio I, Martins B. Using machine learning methods for disambiguating place references in textual documents[J]. GeoJournal, 2015, 80(3):375-392. DOI: 10.1007/s10708-014-9553-y doi: 10.1007/s10708-014-9553-y
[68]	Zhao J, Jin P, Zhang Q, et al. Exploiting location information for web search[J]. Computers in Human Behavior, 2014, 30:378-388. DOI: 10.1016/j.chb.2013.04.023 doi: 10.1016/j.chb.2013.04.023
[69]	Zaila Y L, Montesi D. Geographic information extraction, disambiguation and ranking techniques[C]. Proceedings of the 9th Workshop on Geographic Information Retrieval, 2015:1-7. DOI: 10.1145/2837689.2837695 doi: 10.1145/2837689.2837695
[70]	武汉理工大学. 一种基于时间地理学的游记地名消歧方法[P]. 发明专利,202010495378.9. 2020-06-03.
	[ Wuhan University of Technology. A method for disambiguation of Travel notes and place names based on time geography[P]. Patent, 202010495378.9. 2020-06-03. ]
[71]	侯东阳, 武昊, 陈军. 时空数据Web搜索的研究进展[J]. 地理信息世界, 2020, 27(4):1-12,21.
	[ Hou D Y, Wu H, Chen J. Research Progress on searching spatiotemporal data from Web[J]. Geomatics World, 2020, 27(4):1-12,21. ] DOI: 10.3969/j.issn.1672-1586.2020.04.001 doi: 10.3969/j.issn.1672-1586.2020.04.001
[72]	Silva M J, Martins B, Chaves M, et al. Adding Geographic Scopes to Web Resources[J]. Computers environment urban systems, 2006, 30(4):378-399. DOI: 10.1016/j.compenvurbsys.2005.08.003 doi: 10.1016/j.compenvurbsys.2005.08.003
[73]	Hao C, Winter S, Vasardani M. Georeferencing places from collective human descriptions using place graphs[J]. Journal of Spatial Information Science, 2018, 2018(17):31-62. DOI: 10.5311/JOSIS.2018.17.417 doi: 10.5311/JOSIS.2018.17.417
[74]	Al-Olimat H S, Shalin V L, Thirunarayan K, et al. Towards geocoding spatial expressions (vision paper)[C]. Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019:75-78. DOI: 10.13140/RG.2.2.28807.04007 doi: 10.13140/RG.2.2.28807.04007
[75]	马广迪, 杨为琛. 基于CNN-CBIR的遥感图像分类检索方法[J]. 北京测绘, 2021, 35(5):6.
	[ Ma G D, Yang W C. Remote sensing image classification and retrieval method based on CNN-CBIR[J]. Beijing Surveying and Mapping, 2021, 35(5):6. ] DOI: 10.19580/j.cnki.1007-3000.20 21.05.014 doi: 10.19580/j.cnki.1007-3000.20 21.05.014
[76]	李向阳, 庄越挺, 潘云鹤. 基于内容的图像检索技术与系统[J]. 计算机研究与发展, 2001, 38(3):344-354.
	[ Li X, Zhuang Y T, Pan Y P. The technique and systems of content basedimage retrieval[J]. Journal of Computer Research and Development, 2001, 38(3):344-354. ] DOI: 10.3969/j.issn.2095-2104.2013.21.644 doi: 10.3969/j.issn.2095-2104.2013.21.644
[77]	Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110. DOI: 10.1023/B:VISI.0000029664.99 615.94 doi: 10.1023/B:VISI.0000029664.99 615.94
[78]	Bay H, Ess A, Tuytelaars T, et al. Speeded-Up Robust Features (SURF)[J]. Computer Vision Image Understanding, 2008, 110(3):346-359. DOI: 10.1016/j.cviu.2007.09.014 doi: 10.1016/j.cviu.2007.09.014
[79]	Perd'och M, Chum O, Matas J. Efficient representation of local geometry for large scale object retrieval[C]. 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009:9-16. DOI: 10.1109/CVPR.2009.5206529 doi: 10.1109/CVPR.2009.5206529
[80]	Razavian A S, Sullivan J, Carlsson S, et al. Visual instance retrieval with deep convolutional networks[J]. ITE Transactions on Media Technology Applications, 2016, 4(3):251-258. DOI: 10.3169/mta.4.251 doi: 10.3169/mta.4.251
[81]	Babenko A, Lempitsky V. Aggregating deep convolutional features for image retrieval[J]. arXiv:1510.07493, 2015.
[82]	Tolias G, Sicre R, Jégou H. Particular object retrieval with integral max-pooling of CNN activations[C]. ICLR 2016 - International Conference on Learning Representations, 2016:1-12. HAL Id: hal-01842218
[83]	Radenović F, Tolias G, Chum O. Fine-tuning CNN image retrieval with no human annotation[J]. IEEE transactions on pattern analysis machine intelligence, 2018, 41(7):1655-1668. DOI: 10.1109/TPAMI.2018.2846566 doi: 10.1109/TPAMI.2018.2846566
[84]	Chu T, Chen Y, Huang L, et al. A Grid Feature-Point Selection Method for Large-Scale Street View Image Retrieval Based on Deep Local Features[J]. Remote Sensing, 2020, 12(23):3978. DOI: 10.3390/rs12233978 doi: 10.3390/rs12233978
[85]	Cao B, Araujo A, Sim J. Unifying deep local and global features for image search[C]. European Conference on Computer Vision, 2020:726-743. DOI: 10.1007/978-3-030-58565-5_43 doi: 10.1007/978-3-030-58565-5_43
[86]	Mihalcea R, Tarau P. Textrank: Bringing order into text[C]. Proceedings of the 2004 conference on empirical methods in natural language processing, 2004:404-411.
[87]	Jalilifard A, Caridá V F, Mansano A F, et al. Semantic Sensitive TF-IDF to Determine Word Relevance in Documents[M]. Advances in Computing and Network Communications. Springer, Singapore, 2021:327-337. DOI: 10.1007/978-981-33-6987-0_27 doi: 10.1007/978-981-33-6987-0_27
[88]	Wei X, Croft W B. LDA-based document models for ad-hoc retrieval[C]. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 2006:178-185. DOI: 10.1145/1148170.1148204 doi: 10.1145/1148170.1148204
[89]	Fu X, Li J, Yang K, et al. Dynamic online HDP model for discovering evolutionary topics from Chinese social texts[J]. Neurocomputing, 2016, 171:412-424. DOI: 10.1016/j.neucom.2015.06.047 doi: 10.1016/j.neucom.2015.06.047
[90]	王坤, 尹章才, 应申, 等. 一种基于地理要素类型的语义关系计算方法[J]. 地理信息世界, 2018, 25(5):55-60.
	[ Wang K, Yin Z C, Yin Z, et al. A semantic relation calculation method based on geographic feature types[J]. Geomatics World, 2018, 25(5):55-60. ] DOI: 10.3969/j.issn.1672-1586.2018.05.010 doi: 10.3969/j.issn.1672-1586.2018.05.010
[91]	Bs A, Peng Y, Zy A, et al. A stream computing approach for live environmental models using a spatial data infrastructure with a waterlogging model case study[J]. Environmental Modelling Software, 2019, 119:182-196. DOI: 10.1016/j.envsoft.2019.06.009 doi: 10.1016/j.envsoft.2019.06.009
[92]	Wang Y, Gui Z, Wu H, et al. Optimizing and accelerating space-time Ripley's K function based on Apache Spark for distributed spatiotemporal point pattern analysis[J]. Future Generation Computer Systems, 2019, 105:96-118. DOI: 10.1016/j.future.2019.11.036 doi: 10.1016/j.future.2019.11.036
[93]	Yue P, Gao F, Shangguan B, et al. A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing[J]. International Journal of Geographical Information Science, 2020, 34(2):1-32. DOI: 10.1080/13658816.2020.1730850 doi: 10.1080/13658816.2020.1730850
[94]	Li H, Chen Y, Deng S, et al. Eigenvector spatial filtering-Based logistic regression for landslide susceptibility assessment[J]. International Journal of Geo-Information, 2019, 8(8):24. DOI: 10.3390/ijgi8080332 doi: 10.3390/ijgi8080332
[95]	程朋根, 岳琛, 朱欣焰. 多源数据支持下的城市生态环境评价及其与人类活动关系的研究[J]. 武汉大学学报·信息科学版, 2021,1-14.
	[ Cheng P G, Yue C, Zhu X Y. Evaluation of urban ecological environment and its relationship with human activities based on Multi-Source data[J]. Geomatics and Information Science of Wuhan University, 2021,1-14. ] DOI: 10.13203/j.whugis20200382 doi: 10.13203/j.whugis20200382

Global Location Information Superposition Protocol and Location-based Service Network Technology: Progress and Prospects

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