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检索条件"机构=Key Laboratory of Data Engineering and Knowledge Services"

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Enable Privacy Preservation for k-NN Query in Two-tiered Wireless Sensor Networks

Enable Privacy Preservation for k-NN Query in Two-tiered Wir...

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IEEE International Conference on Communications

作者： Hui Peng Xiaoying Zhang Hong Chen Yao Wu Juru Zeng Deying Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China

ISBN: (纸本)9781467364300

Wireless sensor network is an important part of the Internet of Things. Preservation of privacy and integrity in wireless sensor networks is extremely urgent and challenging. To address this problem, we propose PPKN, an efficient and privacy-preserving k-NN query protocol in two-tiered wireless sensor networks. Our proposal prevents adversaries from gaining sensitive information of both queries issued by users and data collected by sensor nodes while allows the sink to verify whether results are valid. It offers confidentiality of queries and data by constructing a special code, provides integrity verification by the correlation among data. Moreover, by the implementation of KNQ query framework, PPKN also achieves high efficient in query response and energy consumption. Finally, the theoretical analysis and experiment results show the high performance of PPKN in terms of privacy preservation and query efficiency.

关键词： Wireless sensor networks Energy consumption data privacy Privacy Protocols Cryptography Storage management

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Tri-level combination for image representation 17th

Tri-level combination for image representation

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Ruiying Zhang, Chunjie Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319488899

The context of objects can provide auxiliary discrimination beyond objects. However, this effective information has not been fully explored. In this paper, we propose Tri-level Combination for Image Representation (TriCoIR) to solve the problem at three different levels: object intrinsic, strongly-related context and weakly-related context. Object intrinsic excludes external disturbances and more focuses on the objects themselves. Strongly-related context is cropped from the input image with a more loose bound to contain surrounding context. Weaklyrelated one is recovered from the image other than object for global context. First, strongly and weakly-related context are constructed from input images. Second, we make cascade transformations for more intrinsical object information, which depends on the consistency between generated global context and input images in the regions other than object. Finally, a joint representation is acquired based on these three level features. The experiments on two benchmark datasets prove the effectiveness of TriCoIR. © Springer International Publishing AG 2016.

关键词： Image representation

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Fast incremental structure from motion based on parallel bundle adjustment

Fast incremental structure from motion based on parallel bun...

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作者： Cao, Mingwei Zheng, Liping Jia, Wei Liu, Xiaoping Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of Technology Hefei230009 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China

Structure from motion has attracted a lot of research in recent years, with new state-of-the-art approaches coming almost every year. One of its advantages over 3D reconstruction is that it can be used for any cameras (UAVs, depth sensor, light field) and produces relatively accurate point clouds and camera parameters. One of its disadvantages compared to other approaches is that it is computationally expensive. In this paper, we design a novel structure-from-motion framework to reduce the computational cost and implement a parallel bundle adjustment on GPU device for large-scale optimization. In our framework, the local bundle adjustment is added into the architecture of the incremental structure from motion;namely, the point clouds and camera’s parameters are optimized when an additional number of images was added. Then, the purpose is not only to improve the quality of the produced point clouds but also to reduce computation time via parallel bundle adjustment. We conduct extensively experiments on several challenging datasets and make comparison with the state-of-the-art methods. Experimental results show that the proposed method has the best performance in terms of accuracy and efficiency. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Cameras

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SWEE: Approximately searching web service with keywords effectively and efficiently

SWEE: Approximately searching web service with keywords effe...

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The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

作者： Zuoyan Qin Peng Li Qing Zhu Chao Tian Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing 100872

ISBN: (纸本)9781424458455;9781424458486;9781424458479;9781424458462

With the wide use of web services over the world, an effective and efficient search engine becomes necessary. In this paper, we analyzed the limitation of search method using traditional UDDI, and make it in LR-sryle and take advantage of approximate string matching. Motivated by the feature of WSDL files which define the interfaces of web services, we make operations defined in WSDL files which compose web services as the base units for searching and organize all information of operations and corresponding components as documents, which will facilitate IRStyle keyword searching. In order to improve the precision of searching, we enable users to specify weights in their queries. By defining our ranking function, we sort all the results and present top n ones to users. We also build inverted indexes on operations and corresponding documents to improve query efficiency. In addition, we carry out simple semantic analysis on WSDL files. to acquire better accuracy. At last, not only have we tested the efficiency of query after introducing approximate string matching, but also have we verified the effectiveness of the query results.

关键词： Web Service Search engines String matching fundamental units Consumers Search methods Searches keyWORD Surgery

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Greedy-Algorithm of KSORD Supporting Multi-language Phrase Recognition

Greedy-Algorithm of KSORD Supporting Multi-language Phrase R...

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International Conference on Advanced Computer Theory and engineering, ICACTE

作者： Peng Li Qing Zhu Chao Tian Shan Wang Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing China

With the rapid development of information retrieval technology and daily increasing information in the Internet, common users can retrieve many text-based database and get part of the information through the search engines such as Google, and Baidu. However, there is a great amount of data contained in the background relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison between our algorithm and the existing ones. The experiment results shows that our algorithm owns not only the feature of effectiveness but also the feature of efficiency.

关键词： Relational databases Internet Information retrieval data engineering knowledge engineering Search engines Dictionaries data structures Chaos Laboratories

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PIE: A Personalized Incentive for Location-aware Mobile Crowd Sensing

PIE: A Personalized Incentive for Location-aware Mobile Crow...

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IEEE Symposium on Computers and Communications

作者： Yao Wu Yuncheng Wu Juru Zeng Hong Chen Cuiping Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing China

Mobile crowd sensing has the potential to acquire massive data from places and address large-scale societal problems. However, most currently existing crowd sensing systems suffer from insufficient participants. Therefore, incentive design for crowd sensing is essential and urgent. In this paper, different from the auction-based and server-dominant incentives, we design a personalized incentive, PIE, with partiality for neither the server nor the participants with budget constraint. The total payment for all the participants accords to their collective participation level, and the individual reward for each participant depends on individual contribution. We measure the individual contribution and participation level based on Voronoi diagram and Shannon entropy. Both offline and online incentives are proposed with budget constraint. Experimental study shows that our incentives are participation-aware and contribution-dependent, which encourages participants' active join, balanced distribution and flexible reward.

关键词： Sensors Servers Atmospheric measurements Particle measurements Entropy Mobile communication Computational modeling

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The Electronic Records Management in E-government Strategy: Case Studies and the Implications

The Electronic Records Management in E-government Strategy: ...

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International Conference on Networking and Digital Society, ICNDS

作者： Xiaomi An Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing China

Electronic records management (ERM) is fundamental to good governance, business efficiency and effectiveness of e-government in networking and digital society. However, government authorities in China has faced many challenges in managing electronic records. A study of ERM in e-government strategy in other countries would be significant to support development of ERM in Chinese e-government strategy. As little is known from literature on the status of electronic records management in e-government strategy, this paper selects U.S, New Zealand and UK for case study by means of collecting and analyzing publications, laws, regulations and policies relevant to both electronic records management and e-government strategy. The author first analyzes status of ERM in e-government strategy and then discusses models and driving forces of their existences. The result of the study revealed that electronic records are managed as national assets, resources and trusted information in the e-government strategy. Driven by core business of e-government in different country, there are different approaches to ERM in e-government strategy. The implications of the study is that, to position ERM in e-government strategy, it is significant to provide a strategic approach to ERM for shared agenda by both government authorities and records management professionals. The findings intended to be of use to both the effective e-government strategy and good ERM for dynamic, interactive and proactive citizen-centered services across domains and time dimensions.

关键词： Electronic government Conference management knowledge management engineering management Law data engineering knowledge engineering Asset management Resource management Sustainable development

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A Framework for Personalized Management of Domain Ontologies

A Framework for Personalized Management of Domain Ontologies

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International Conference on Computer and Information Science (ACIS)

作者： Runnan Liu Puwei Wang Shixian Zheng Key Laboratory of Data Engineering and Knowledge Engineering of the Ministry of Education Renmin University of China Beijing China

As the sharable and reusable domain knowledge, domain ontology increasingly serves as a foundation for semantic Web. Personalized management of domain ontologies is to provide personalized views of domain ontologies to users during run time according to user preferences. It helps that users can focus on their interested parts, instead of the whole. It increases the efficiency of ontology-based application. This paper proposes a framework for personalized management of domain ontologies. In this framework, a user model firstly is introduced to describe user preferences. Secondly, domain ontologies are decomposed into moderate-scale modules with high cohesion and low coupling. During run time, modules that a user is interested in are selected out based on the user's preferences. Finally, the selected modules are combined to construct personalized views of domain ontologies for the user.

关键词： Ontologies Conferences Cognition Semantics Vectors Semantic Web

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Fast & scalable distributed set similarity joins for big data analytics 33

Fast & scalable distributed set similarity joins for big dat...

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33rd IEEE International Conference on data engineering, ICDE 2017

作者： Rong, Chuitian Lin, Chunbin Silva, Yasin N. Wang, Jianguo Lu, Wei Du, Xiaoyong Tianjin Polytechnic University China Arizona State University United States University of California San Diego United States Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China

ISBN: (纸本)9781509065431

Set similarity join is an essential operation in big data analytics, e.g., data integration and data cleaning, that finds similar pairs from two collections of sets. To cope with the increasing scale of the data, distributed algorithms are called for to support large-scale set similarity joins. Multiple techniques have been proposed to perform similarity joins using MapReduce in recent years. These techniques, however, usually produce huge amounts of duplicates in order to perform parallel processing successfully as MapReduce is a shared-nothing framework. The large number of duplicates incurs on both large shuffle cost and unnecessary computation cost, which significantly decrease the performance. Moreover, these approaches do not provide a load balancing guarantee, which results in a skewness problem and negatively affects the scalability properties of these techniques. To address these problems, in this paper, we propose a duplicate free framework, called FS-Join, to perform set similarity joins efficiently by utilizing an innovative vertical partitioning technique. FS-Join employs three powerful filtering methods to prune dissimilar string pairs without computing their similarity scores. To further improve the performance and scalability, FS-Join integrates horizontal partitioning. Experimental results on three real datasets show that FS-Join outperforms the state-of-Theart methods by one order of magnitude on average, which demonstrates the good scalability and performance qualities of the proposed technique. © 2017 IEEE.

关键词： MapReduce

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Factors affecting knowledge transfer from pre-retirees to younger employees

Factors affecting knowledge transfer from pre-retirees to yo...

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International Conference on services Systems and services Management, ICSSSM

作者： Changyu Wang Meiyun Zuo Yifan Bo Key Laboratory of Data Engineering and Knowledge Engineering and School of Business Renmin University of China Beijing China

knowledge transfer is an important type of knowledge service. Based on existing studies on knowledge transfer between employees, this paper builds a research model of factors affecting the pre-retiree's intention to transfer knowledge to the younger employee. data collected from 4 leaders and 7 pre-retirees in different industries through face-to-face interview is used to test and improve the model, then we gain a theoretical model which posits that the pre-retiree's knowledge transfer intention is influenced by the pre-retiree's perceptions of younger employees and emotions to organization, the younger employee's attitudes towards pre-retirees, the younger employee's learning intention and ability and work attitudes, communication difference between the pre-retiree and the younger employee. Our results contribute to the improvement of research on pre-retirees' knowledge transfer and have implications for management practices.

关键词： knowledge transfer Interviews Organizations data models Educational institutions Analytical models Cognition

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