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Cloud detection from visual band of satellite image based on variance of fractal dimension

Journal of Systems engineering and Electronics 2019年第3期30卷 485-491页

作者： TIAN Pingfang GUANG Qiang LIU Xing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-Time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-Media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

关键词： cloud detection visual image satellite image variance of local fractal dimension (VLFD)

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VID Join： Mapping Trajectories to Points of Interest to Support Location-Based Services

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Journal of Computer Science & Technology 2015年第4期30卷 725-744页

作者：商烁谢珂心郑凯刘家俊文继荣 Department of Computer Science China University of Petroleum Beijing 102249 China School of Information Technology and Electrical Engineering The University of Queensland Brisbane QLD 4072 Australia School of Computer Science and Technology Soochow University Suzhou 215006 China Commonwealth Scientific and Industrial Research Organisation Kenmore QLD 4069 Australia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100080 China

Variable influence duration （VID） join is a novel spatio-temporal join operation between a set T of trajectories and a set P of spatial points. Here, trajectories are traveling histories of moving objects （e.g., travelers）, and spatial points are points of interest （POIs, e.g., restaurants）. VID join returns all pairs of （τs, p） if τs is spatially close to p for a long period of time, where τs is a segment of trajectory τ ∈ T and p ∈ P. Each returned （τs, p） implies that the moving object associated with τs stayed at p （e.g., having dinner at a restaurant）. Such information is useful in many aspects, such as targeted advertising, social security, and social activity analysis. The concepts of influence and influence duration are introduced to measure the spatial closeness between τ and p, and the time spanned, respectively. Compared to the conventional spatio-temporal join, the VID join is more challenging since the join condition varies for different POIs, and the additional temporal requirement cannot be indexed effectively. To process the VID join e？ciently, three algorithms are developed and several optimization techniques are applied, including spatial duplication reuse and time duration based pruning. The performance of the developed algorithms is verified by extensive experiments on real spatial data.

关键词： trajectory spatial database spatial join spatio-temporal join

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Few-Shot Charge Prediction with Multi-grained Features and Mutual Information 20

Few-Shot Charge Prediction with Multi-grained Features and M...

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20th China National Conference on Computational Linguistics, CCL 2021

作者： Zhang, Han Dou, Zhicheng Zhu, Yutao Wen, Jirong School of Information Renmin University of China Beijing China Gaoling School of Artificial Intelligence Renmin University of China Beijing China Université de Montréal Montreal Canada Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China

ISBN: (纸本)9783030841850

Charge prediction aims to predict the final charge for a case according to its fact description and plays an important role in legal assistance systems. With deep learning based methods, prediction on high-frequency charges has achieved promising results but that on few-shot charges is still challenging. In this work, we propose a framework with multi-grained features and mutual information for few-shot charge prediction. Specifically, we extract coarse- and fine-grained features to enhance the model’s capability on representation, based on which the few-shot charges can be better distinguished. Furthermore, we propose a loss function based on mutual information. This loss function leverages the prior distribution of the charges to tune their weights, so the few-shot charges can contribute more on model optimization. Experimental results on several datasets demonstrate the effectiveness and robustness of our method. Besides, our method can work well on tiny datasets and has better efficiency in the training, which provides better applicability in real scenarios. © 2021, Springer Nature Switzerland AG.

关键词： Forecasting

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A Comparative Analysis of knowledge Management Methods in the Three knowledge Management Standards

A Comparative Analysis of Knowledge Management Methods in th...

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2012年管理与服务科学国际会议(MASS 2012)

作者： Shaotong Xu Xiaomi An Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China) MOE

This paper aims to identify knowledge management (KM) methods that have been used in three KM Standards, i.e. KM Standards of Britain, European Union(EU) and Australia, with comparative analysis of three KM issues covering: basic definitions, KM work processes, essential factors and management frameworks;with a chronological analysis of their characteristics and evolution. The studies find that along with the practical development of KM practices, concepts of KM are getting understood more and more broadly, ranges of KM activities are extending, but management factors are getting highly integrated, and the management frameworks are going towards ecosystem. The paper provides valuable insight on theoretical and practical development of knowledge management methods and standards.

关键词： knowledge management knowledge management method knowledge management standard

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Sparse Topic Model for text classification

Sparse Topic Model for text classification

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tao Liu Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE

ISBN: (纸本)9781479902590

This paper addresses a new text classification method: Sparse Topic Model, which represents documents by the sparse coding of topics. Topics contain more semantic information than words, so it's more effective for feature representation of documents. Topics are extracted from documents by LDA in an unsupervised way. Based on these topics, sparse coding is applied to discover more high-level representation. We compare the Sparse Topic Model with the traditional methods, such as SVM, and the experimental result show that the proposed method achieves better performance, especially when the number of training examples is limited. The effect of topic number and word number per topic on the performance is also investigated. Due to the unsupervised characteristic of Sparse Topic Model, it's very useful for real application.

关键词： Support vector machines Text categorization Abstracts Semantics Petroleum

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CitationAS： A Tool of Automatic Survey Generation Based on Citation Content

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Journal of data and Information Science 2018年第2期3卷 20-37页

作者： jie wang chengzhi zhang mengying zhang sanhong deng School of Information Management Nanjing University Nanjing 210023 China Department of Information Management Nanjing University of Science and Technology Nanjing 210094 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Purpose： This study aims to build an automatic survey generation tool, named CitationAS, based on citation content as represented by the set of citing sentences in the original ***/methodology/approach： Firstly, we apply LDA to analyse topic distribution of citation content. Secondly, in CitationAS, we use bisecting K-means, Lingo and STC to cluster retrieved citation content. Then Word2Vec, Word Net and combination of them are applied to generate cluster labels. Next, we employ TF-IDF, MMR, as well as considering sentence location information, to extract important sentences, which are used to generate surveys. Finally, we adopt manual evaluation for the generated ***： In experiments, we choose 20 high-frequency phrases as search terms. Results show that Lingo-Word2Vec, STC-Word Net and bisecting K-means-Word2Vec have better clustering effects. In 5 points evaluation system, survey quality scores obtained by designing methods are close to 3, indicating surveys are within acceptable limits. When considering sentence location information, survey quality will be improved. Combination of Lingo, Word2Vec, TF-IDF or MMR can acquire higher survey *** limitations： The manual evaluation method may have a certain subjectivity. We use a simple linear function to combine Word2Vec and Word Net that may not bring out their strengths. The generated surveys may not contain some newly created knowledge of some articles which may concentrate on sentences with no *** implications： CitationAS tool can automatically generate a comprehensive, detailed and accurate survey according to user’s search terms. It can also help researchers learn about research status in a certain ***/value： Citaiton AS tool is of practicability. It merges cluster labels from semantic level to improve clustering results. The tool also considers sentence location information when calculating sentence score by TF-IDF and MMR.

关键词： Automatic survey system Citation content Clustering algorithms Labelgeneration approaches Sentence extraction methods

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Rapid resynchronization method for replication in-memory databases supporting mobile communication applications

Rapid resynchronization method for replication in-memory dat...

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2009 WRI World Congress on Computer Science and Information engineering, CSIE 2009

作者： Guoqiong, Liao Jing, Li School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 Thailand Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 Thailand

ISBN: (纸本)9780769535074

In this paper, a rapid resynchronization method using intent logs is suggested for replication In-memory databases supporting mobile communication applications. Both the identifiers of unsynchronized segments and the identifiers of the slaves who have missed the updates in the segments are recorded in the intent logs. When receiving a resynchronization request from a slave, the master will scan the intent logs to find the unsynchronized segments for the salve, and then send the segments gotten directly from its memory to the slave. The performance results shown the intent logs method can reduce resynchronization time than methods using transaction logs. © 2008 IEEE.

关键词： Mobile telecommunication systems

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Collaborative innovation community capacity building for electronic records security management 17

Collaborative innovation community capacity building for ele...

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17th International Conference on Intellectual Capital, knowledge Management and Organisational Learning, ICICKM 2020

作者： Wang, Lili An, Xiaomi Xu, Jicang Huang, Jie Guo, Mingjun Hu, Jufang School of Information Resource Management Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing China Renmin University of China Libraries Beijing China

ISBN: (纸本)9781912764723

With more and more governmental business going digital and collaborative to the best of whole government value and public value, electronic records security management (ERSM) faces great challenges. There is a growing understanding that standardization is the key to the successful ERSM, when governmental business requires cross-boundary collaboration. However, previous studies of collaborative innovation community capacity building (CICCB) on ERSM are mainly from the perspective of archival study to the best of long term preservation of electronic archives,with little concerns about needs of different interested parties. Few studies have been taken from interdisciplinary perspective and integrated use of international standards of business continuity management, records management, knowledge management and information security management to the best value of knowledge sharing and continuity of business, records, knowledge and security service. Based on prior findings and the integrated use of ISO management systems standards (ISO/IEC 27001, 2013;ISO 15489-1, 2016;ISO 30401, 2018;ISO 22301, 2019;ISO 30301, 2019), this study analyses the motivation mechanisms of CICCB for ERSM, then develops an extended conceptual framework for CICCB, including cognitive collaboration which means shared knowledge and values on ERSM for all types of interested parties that enable continual improvement;interested parties collaboration which means human interactions on shared rules for community practice on ERSM that enable improved transparency and accountability;process collaboration which means shared standards, guidelines and models for whole process control that enable electronic records controllable with characteristics of authenticity, reliability, integrity, usability, confidentiality and availability;technical collaboration which means shared solutions that enable electronic records systems reliable, secure, compliant, comprehensive, systematic. The above collaborations need com

关键词： knowledge management

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RGB-D Visual Odometry Based on Semantic Feature Points in Dynamic Environments 1st

RGB-D Visual Odometry Based on Semantic Feature Points in ...

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1st CAAI International Conference on Artificial Intelligence, CICAI 2021

作者： Wang, Hao Wang, Yincan Fang, Baofu Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Anhui230009 China School of Computer Science and Information Engineering HeFei University of Technology Anhui Hefei230009 China

ISBN: (纸本)9783030930486

Various algorithms of traditional visual Simultaneous Localization and Mapping (SLAM) can well match with static scenes, but mismatches will occur in dynamic scenes, which makes the positioning and mapping of the SLAM system produce large errors. Therefore, this paper proposed a visual odometry algorithm based on semantic feature points, which can improve the positioning accuracy in dynamic scenes. The algorithm combined semantic information to detect dynamic objects, and then detects and eliminates dynamic feature points. This paper conducted an extensive evaluation of the system and compared it with ORB-SLAM3 and other dynamic scene SLAM systems. The experimental results show that this method greatly improves the positioning accuracy of the camera and the robustness of the system in a highly complex dynamic environment, which verifies the advancement and effectiveness of the algorithm in this paper. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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Publish me and protect me: Personalized and flexible location privacy protection in mobile social networks

Publish me and protect me: Personalized and flexible locatio...

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International Workshop on Quality of Service

作者： Yao Wu Hui Peng Xiaoying Zhang Hong Chen Cuiping Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing China

With the increasing proliferation of the Mobile Social Networks (MSN) and the Location Based Service (LBS), location privacy has attracted broad attention in recent years. Most researches have been done with the assumption that the server is untrusted and a trusted third party is introduced to protect the user location privacy when a user sends queries for the location service. In this paper, we reconsider this assumption and propose a Personalized and Flexible location privacy protection Model (PFM) based on user relationship strength. We conduct researches in the situation that the server is trusted while malicious users in the MSN can disguise as a friend to break location privacy. We present an entropic TF-IDF based approach to measure the bi-directional relationship strength and propose probability distribution based cloaking model to protect user location privacy. We thoroughly evaluate our methods based on Quality of Privacy (QoP) via real and synthetic data.

关键词： Legged locomotion Weight measurement

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