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Methodology, progress and challenges of geoscience knowledge graph in International Big science Program of Deep-Time Digital Earth

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Journal of Geographical sciences 2025年第5期35卷 1132-1156页

作者： ZHU Yunqiang WANG Qiang WANG Shu SUN Kai WANG Xinbing LV Hairong HU Xiumian ZHANG Jie WANG Bin QIU Qinjun YANG Jie ZHOU Chenghu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCAS Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application University of Chinese Academy of Sciences School of Electronic Information and Electrical EngineeringShanghai Jiao Tong University Department of Automation Tsinghua University State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing University State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Command Center of Natural Resources Comprehensive Survey School of Computer Science China University of Geosciences

Deep-time Earth research plays a pivotal role in deciphering the rates, patterns, and mechanisms of Earth's evolutionary processes throughout geological history, providing essential scientific foundations for climate prediction, natural resource exploration, and sustainable planetary stewardship. To advance Deep-time Earth research in the era of big data and artificial intelligence, the International Union of Geological sciences initiated the “Deeptime Digital Earth International Big science Program”(DDE) in 2019. At the core of this ambitious program lies the development of geoscience knowledge graphs, serving as a transformative knowledge infrastructure that enables the integration, sharing, mining, and analysis of heterogeneous geoscience big data. The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1) establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2) developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3) implementing a comprehensive three-tiered architecture encompassing basic, discipline-specific, and application-oriented knowledge graphs, spanning approximately 20 geoscience disciplines. Through its open knowledge framework and international collaborative network, this initiative has fostered multinational research collaborations, establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable, Accessible, Interoperable, Reusable) data practices in deep-time Earth systems research.

关键词： Deep-time Digital Earth International Big science Program deep-time Earth geoscience knowledge graph

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FS-Net: Medical image denoising via local receptive field smoothing network 4

FS-Net: Medical image denoising via local receptive field sm...

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4th IEEE International Conference on Data science in Cyberspace, DSC 2019

作者： Xiaowei, Wang Xiong, Jiaxin Wang, Rui Sori, Worku J. Wang, Jingtian Shaohui, Liu Jiang, Feng Command Automation College PLA Army Engineering University Nanjing210007 China School of Computer Beijing Institute of Technology Beijing China School Of Architecture Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China Mary Star of the Sea High School CA90731 United States School of Computer Science Jinling Hospital Nanjing China Harbin210002 China

ISBN: (纸本)9781728145280

Noise is one of the most challenging tasks in medical images which is happening during transmission and acquisition, and as a result, it complicates a subsequent medical image analysis task. This paper proposes a novel local receptive field smoothing network (FS-Net) for medical image denoising by introducing smoothing priors of receptive field of intermediate CNN layers. First, for a receptive field of a CNN, each of its values smoothing properties are retained by weighting their local neighborhoods (i.e., after smoothing, each new neurons are the weighted average of its neighborhoods). The weights are calculated using the similarity of their corresponding receptive field (i.e., the similarity between the receptive field used to calculate a receptive fields value and the receptive field used to calculate their corresponding neighborhoods) and this keeps the smoothing properties. Second, by applying this smoothing prior on receptive fields of intermediate CNN layers, an end to end FSNet which directly approximate the latent clean images from its noisy version is designed. The receptive fields smoothing helps to train deeper architecture and improves the reconstructed image quality. Experimental results on Breast Mammography images reveal that the proposed method outperforms other states of the art denoising methods. © 2019 IEEE.

关键词： Image denoising

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FS-Net: Medical Image Denoising via Local Receptive Field Smoothing Network

FS-Net: Medical Image Denoising via Local Receptive Field Sm...

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IEEE International Conference on Data science in Cyberspace (DSC)

作者： Wang Xiaowei Jiaxin Xiong Rui Wang Worku J. Sori Jingtian Wang Liu Shaohui Feng Jiang Command Automation College PLA Army Engineering University Nanjing China School of Computer Beijing Institute of Technology Beijing China School of Architecture Harbin Institute of Technology) Harbin China School of Computer Science and Technology Harbin institute of technology Harbin China Mary Star of the Sea High School CA USA School of Computer Science and Jinling Hospital Harbin China

关键词： Smoothing methods Image denoising Medical diagnostic imaging Noise reduction Noise measurement Computational modeling

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Interaction and collective intelligence on the internet

Interaction and collective intelligence on the internet

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9th Annual Conference on Theory and Applications of Models of Computation, TAMC 2012

作者： Li, Deyi Huang, Liwei Department of Computer Science and Technology Tsinghua University Beijing 100084 China Institute of Command Automation PLA University of Science and Technology Nanjing 210007 China

ISBN: (纸本)9783642299513

Network interconnection, information interoperability, and crowds interaction on the Internet could inspire better computation models than Turing machine, since that human plays an important factor in Internet computing, so that the human-machine and machine-machine interactions have evolved to be the kernel of Internet computing. Internet has not been simply equivalent to a virtual huge computer, or a set of computers. On the Internet, human's behaviors are uncertain, the interactions and influence among people are also uncertain. These uncertainties cannot be described by Turing machine and traditional interaction machine. As a new computation platform, Internet computing requires new theories and methods. By combining topology in mathematics with the field theory in physics, we propose the topological potential approach, which set up a virtual field by the topological space to reflect individual activities, local effects and preferential attachments. This approach can be used to research the emergence of collective intelligence. Here, we introduce three case studies to illustrate the analysis on the collective intelligence on the Internet and discuss some potential applications of the topological potential approach. © 2012 Springer-Verlag.

关键词： Turing machines

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A private cloud document management system with document clustering algorithm

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2012 National Conference on Information Technology and computer science, CITCS 2012

作者： Miao, Jiajia Fan, Zhongjun Chen, Guoyou Mao, Handong Wang, Le Institute of Command Automation PLA University of Science and Technology Nanjing China Key Laboratory of C4ISR Technology National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9789491216381

Recently, more and more enterprises use virtualization technology and cloud computing technology to improve the level of information management. Private cloud document management system from the lab to practical application. We launched a private cloud file management system is characterized by the automatic cluster of files, so as to achieve the automated management of the text block. Document clustering has been extensively studied, because it is an effective solution, the organization of a large number of files. In order to overcome the main challenges that the current document clustering a huge number of documents, high dimensional process and comprehensible cluster, we propose a hybrid algorithm based on the top-k frequent itemsets and K-Means. The experimental results show the efficiency and effectiveness of the algorithm is superior to the other two representative clustering algorithm on two public data sets. Our algorithm can be further improved in the future parallel implementation, based on semantic representation and similarity measurement. © 2012. The authors - Published by Atlantis Press.

关键词： Clustering algorithms

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A public opinions monitoring system based on similarity of microblogs

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2012 National Conference on Information Technology and computer science, CITCS 2012

作者： Miao, Jiajia Fang, Xuelin Chen, Guoyou Mao, Handong Wang, Le Institute of Command Automation PLA University of Science and Technology Nanjing China Key Laboratory of C4ISR Technology National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9789491216381

Public opinion is the development and changes in certain social space around the intermediary social events, public social managers and held social and political attitudes. In order to improve the efficiency of text clustering, this paper proposes a new similarity measure model OFM. In the first stage, OFM proposed a new term relationship search algorithm named CrtURG non-directional graphics integrated relationship. OFM build another called SIM expand ad hoc, said vector algorithm to different instant messaging. Keywords expand overlap probability vector increased and instant messages containing specific semantic information. The experimental results show that, OFM, is superior to the combined effect of surface matching methods and corpus-based approaches. © 2012. The authors - Published by Atlantis Press.

关键词： Semantics

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FROM TURING MACHINE INTELLIGENCE TO COLLECTIVE INTELLIGENCE

FROM TURING MACHINE INTELLIGENCE TO COLLECTIVE INTELLIGENCE

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2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems

作者： Liwei Huang Haisu Zhang Guisheng Chen Yuchao Liu Deyi Li Institute of Command Automation PLA University of Science and Technology Academy of National Defense Information Department of Computer Science and Technology Tsinghua University

Almost all of the progress of artificial intelligence in the last 50 years has been based on the Turing model and Von Neumann architecture. Researchers have always tried to put the human intelligence into machines by the ways of algorithms, codes or symbols that could be understood and executed by machines, thus, we may be bounded to Turing model too tightly. In Internet and World Wide Web and developing cloud computing, network has changed the role from a single huge Turing machine or sum of some Turing machines to the collective intelligence, where the inputs or outputs of nodes in network are happening not only among computers, but also among people, such that Internet has been beyond Turing machine. Users in Internet who own similar interests may cluster naturally into scalable and boundless communities with uncertainty, where online interaction avoids the difficulty of common sense representation in traditional artificial intelligence. Furthermore, collective intelligence may emerge from the crowds interaction. Those would become the new research frontiers in intelligence science.

关键词： Turing machine Community in Internet Collective intelligence Social annotation Uncertainty.

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fDSN:Find Dynamic Social Network Over the MicroBlog

fDSN:Find Dynamic Social Network Over the MicroBlog

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2012年互联网技术与应用国际学术会议

作者： Jiajia Miao Xuelin Fang Handong Mao Guoyou Chen Zhongjun Fang Lectuer Institute of Command Automation PLA University of Science and Technology College of Information System and Management National University of Defense Technology Engineer College of Computer National University of Defense Technology Lectuer College of Information System and Management National University of Defense Technology Associate professor Institute of Command Automation PLA University of Science and Technology

Ⅰ.引言近几年,社会媒体的活动达到了一个前所未有的高度,成千上万的用户加入了社会关系网或论坛,注册了微薄并维护自己的web日志。社会媒体的流行催生了大量的商业[1,2]和非商业系统[4,5,6],它们致力于发现社会媒体行为中的重要特征。... 详细信息

Ⅰ.引言近几年,社会媒体的活动达到了一个前所未有的高度,成千上万的用户加入了社会关系网或论坛,注册了微薄并维护自己的web日志。社会媒体的流行催生了大量的商业[1,2]和非商业系统[4,5,6],它们致力于发现社会媒体行为中的重要特征。微博的庞大数据流中包含着大量有价值的信息,为我们提供了机会去挖掘,同时也带来了挑战。首先,也是我们系统所要解决的首要问题,就是如何检测和分析数据流中出现的话题(即舆情)以及如何实时地进行这种检测。舆情往往是受突发事件、爆炸新闻以及大部分Twitter用户共同关心的话题影响的。对于新闻报道者和分析师来说,舆情检测是很有价值的,因为他们需要随时了解最新

关键词： Incremental Algorithm Modularity Community Structure Social Network

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uSM:An Uncertain Schema Mapping Approach Based on Alternative Probabilistic Schemata

uSM:An Uncertain Schema Mapping Approach Based on Alternativ...

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2012年互联网技术与应用国际学术会议

作者： Jiajia Miao Zhongjun Fang Guoyou Chen Xuelin Fang Handong Mao Lectuer Institute of Command Automation PLA University of Science and Technology College of Information System and Management National University of Defense Technology Engineer College of Computer National University of Defense Technology Associate professor Institute of Command Automation PLA University of Science and Technology Lectuer College of Information System and Management National University of Defense Technology

Ⅰ.引言模式匹配的目标就是寻找两个或多个模式的元素之间的语义上的对应关系,属于数据库研究的热点问题[5]。Sheth指出在异构数据库环境下,找出相关对象并解决冲突是实现系统互操作的基本问题之一[6]。文献[7]对现有模式匹配技术进行... 详细信息

Ⅰ.引言模式匹配的目标就是寻找两个或多个模式的元素之间的语义上的对应关系,属于数据库研究的热点问题[5]。Sheth指出在异构数据库环境下,找出相关对象并解决冲突是实现系统互操作的基本问题之一[6]。文献[7]对现有模式匹配技术进行了总结和综述。根据所利用匹配对象信息的不同,模式匹配方法可分为基于模式信息的匹配和基于实例/内容信息的匹配。基于模式信息的匹配只考虑了模式本身的信息,不考虑模式所包含的数

关键词： Schema matching Multi-strategy Uncertain schema Alternative probabilistic

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DiM:Data Instance Matching in Open Source Database System

DiM:Data Instance Matching in Open Source Database System

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2012年互联网技术与应用国际学术会议

作者： Jiajia Miao Guoyou Chen Xing Liu Zhongjun Fang Xuelin Fang Institute of Command Automation PLA University of Science and Technology College of Information System and Management National University of Defense Technology College of Computer National University of Defense Technology

Ⅰ.引言从多种应用场景可以显著看到元组相似性识别与处理是非常关键的,例如采购分析,医疗的数据清理等等。目前已有一些技术被研究,用于以扩展元组相似性操作,如record linkage和join等等用来处理数据中的相似性[3,4]。但在大多数先前... 详细信息

Ⅰ.引言从多种应用场景可以显著看到元组相似性识别与处理是非常关键的,例如采购分析,医疗的数据清理等等。目前已有一些技术被研究,用于以扩展元组相似性操作,如record linkage和join等等用来处理数据中的相似性[3,4]。但在大多数先前的工作中,相似度可识别的操作都与其它常规的或是相似性可识别的操作分开研究。进一步来说,该领域先前的大多数研究都只考虑独立的实现,即没有与任何数据库系统相集成。文献[1]提到的SimDB是一个支持多元相似性可识别操作符的相似性可识别的数据库系统,考虑在数据库系统中进行元组相似性识别和处理是可

关键词： Instance matching Maximum entropy model String distance Similarity Join

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