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Concepts and methods of cyberspace geographic map
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CHEN Shuai, GUO Qiquan, GAO Chundong, HAO Mengmeng, JIANG Dong, NI Shiyuan, NI Tao
Science & Technology Review | 2023, 41(13) : 14 - 22
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Science & Technology Review | 2023, 41(13): 14-22
Exclusive: Theory and Application of Cyberspace Geography
Concepts and methods of cyberspace geographic map
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CHEN Shuai, GUO Qiquan, GAO Chundong, HAO Mengmeng, JIANG Dong, NI Shiyuan, NI Tao
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Published: 2023-07-13 doi: 10.3981/j.issn.1000-7857.2023.13.002
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Map is an effective tool to recognize real space. Cyberspace also needs abstract, symbolic and numerical maps for visualization and cognition. Based on a comprehensive review of existing theories and methods on cyberspace map and from a perspective of visual representation of cyberspace elements and cyberspace knowledge, the current study proposes a concept and connotation of the cyberspace geographic map by synthesizing the concept of“tupu” in both computer science and geography.. Besides, this study introduces the methods and key technologies for cyberspace geographic map construction, and outlooks the application fields from three aspects: cyberspace resource management, cyberspace behavior cognition, and comprehensive analysis of cyberspace events. Mapping the geographical map of cyberspace can associate cyberspace with real space and clearly express the structure of cyberspace. It is a necessary way to realize the cognition of cyberspace behavior and improve the capability of cybersecurity.
geographical space  /  cyberspace  /  cyberspace map  /  knowledge graph  /  cognition of cyberspace
CHEN Shuai, GUO Qiquan, GAO Chundong, HAO Mengmeng, JIANG Dong, NI Shiyuan, NI Tao. Concepts and methods of cyberspace geographic map[J]. Science & Technology Review, 2023 , 41 (13) : 14 -22 . DOI: 10.3981/j.issn.1000-7857.2023.13.002
Year 2023 volume 41 Issue 13
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doi: 10.3981/j.issn.1000-7857.2023.13.002
  • Receive Date:2022-08-13
  • Online Date:2023-08-11
  • Published:2023-07-13
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  • Received:2022-08-13
  • Revised:2022-09-18
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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