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Using mobile phone location data for urban activity analysis

2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013

作者： Xie, Rong Xu, Huizheng Yue, Yang International School of Software Wuhan University 430079 Wuhan China Shenzhen Key Laboratory of High Performance Data Mining 518055 Shenzhen China Shenzhen University Shenzhen China State Key Lab. of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan 430079 China

ISBN: (纸本)9783319040479

Mobile phone data record people's calling logs in everyday life, which reflecting their custom, pattern and lifestyle. In this paper, we present approaches to urban activity analysis from real mobile phone location data, including individual activity analysis and group activity analysis, which can be applied to the field of urban planning and management. © Springer International Publishing Switzerland 2013.

关键词： data mining

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A data-driven approach for convergence prediction on road network

A data-driven approach for convergence prediction on road ne...

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12th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2013

作者： Guo, Qiulei Luo, Jun Li, Guiqing Wang, Xin Geroliminis, Nikolas Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China South China University of Technology Guangzhou China Department of Geomatics Engineering University of Calgary Canada Switzerland

ISBN: (纸本)9783642370861

With the rapid development of location sensing technology such as GPS, huge amount of location data through GPS are produced every day. The flood of taxi GPS data make it possible to predict the plentitude of traffic events on road network. In this paper, we propose a data-driven approach for traffic state convergence prediction on road network. We introduce a new method predicting the future location of taxis on road network. Furthermore we propose a statistical model to predict real time convergence on road network. We experimentally demonstrated that our approach achieves high prediction precision on the real world massive taxi GPS data. © 2013 Springer-Verlag.

关键词： data mining

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Fuzzy control approach to reconfigurable manufacturing system involving equipment representation

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2013 3rd International Conference on Mechanical Science and engineering, ICMSE 2013

作者： Sun, Heng Cai, Shu Bin Massawe, Richard Happson Joseph Department of Computer Science Jinan University Guangzhou 510632 China Software Engineering Department Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China International School Jinan University Guangzhou 510632 China

ISBN: (纸本)9783037857120

The reconfigurable manufacturing system is a cost-effective system that can accommodate a variety of equipments required by customers. However, because of the surprisingly increasing volume and semantically fuzzy nature of the equipment information, one of the main difficulties to realize efficient equipment reconfiguration is the lack of effective equipment representation technologies and semantic description methods. In this paper, a fuzzy ontology model is proposed for storing semantic concepts in the reconfigurable manufacturing system. To discuss fuzzy inference mechanism has indicated that the fuzzy ontology-based method can promote productivity of the reconfigurable manufacturing system. © (2013) Trans Tech Publications, Switzerland.

关键词： Fuzzy control

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A dominating set based approach to identify effective leader group of social network

A dominating set based approach to identify effective leader...

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19th International Computing and Combinatorics Conference, COCOON 2013

作者： Kim, Donghyun Li, Deying Asgari, Omid Li, Yingshu Tokuta, Alade O. Dept. of Mathematics and Computer Science North Carolina Central University Durham NC 27707 United States Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Renmin 100872 China Dept. of Computer Science Georgia State University Atlanta GA 30303 United States

ISBN: (纸本)9783642387678

Very recently, the study of social networks has received a huge attention since we can learn and understand many hidden properties of our society. This paper investigates the potential of social network analysis to select an effective leadership group of a society. Based on our real life observation, we establish three essential requirements for an effective leadership group, namely Influenceability, Partisanship, and Bipartisanship. Then, we formulate the problem of finding a minimum size leader group satisfying the three requirements as the minimum connected k-core dominating set problem (MCkCDSP), and show its NP-hardness. In addition, we introduce an extension of MCkCDSP, namely MCkCDSP-C, which assumes the society has a number of communities and requires at least one representative from each community should be in the leadership. At last, we propose an approximation algorithm for a subclass of MCkCDSP with k = 2, and show an α-approximation algorithm of MCkCDSP can be used to obtain an α-approximation algorithm of MCkCDSP-C. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Approximation algorithms

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Top-k entities query processing on uncertainly fused multi-sensory data

Top-k entities query processing on uncertainly fused multi-s...

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作者： Liu, Dexi Wan, Changxuan Xiong, Naixue Park, Jong Hyuk Rho, Seungmin Jiangxi Key Laboratory of Data and Knowledge Engineering School of Information Technology Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of School of Electrical Engineering Korea University Seoul Korea Republic of

Sensor fusion is the combining of sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The natural uncertainty exists in these data because sensors are not precise enough. Hence, the intuitive method to store this kind of data is using uncertain database. Finding the top-k entities according to one or more attributes is a powerful technique when the uncertain database contains large quantity of data. However, compared to top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. We propose a method to process entity-based global top-k aggregate queries in uncertain database, which returns the top-k entities that have the highest aggregate value. Our method has two levels, entity state generation and G-topk-E query processing. In the former level, entity states, which satisfy the properties of x-tuple, are generated one after the other according to their aggregate values, while in the latter level, dynamic programming-based global top-k entity query processing is employed to return the answers. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions. © 2012 Springer-Verlag London Limited.

关键词： Query processing

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Design of greenhouse gases remote sensing monitoring and validation system and the key technologies

Design of greenhouse gases remote sensing monitoring and val...

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34th Asian Conference on Remote Sensing 2013, ACRS 2013

作者： Miao, Ru Lu, Ning Wang, Juanle Yao, Ling Institute of Data and Knowledge Engineering College of Computer and Information Engineering Henan University Jin Ming Avenue Kaifeng Henan 475004 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences 11A Datun Road Chaoyang District Beijing 100101 China

ISBN: (纸本)9781629939100

Greenhouse gases remote sensing monitoring system is implementation of greenhouse gases remote sensing applied technologies. This paper discusses the business application mode, operation scheme and application technology system of greenhouse gases remote sensing monitoring based on multi-source remote sensing data. The system analysis of greenhouse gases remote sensing monitoring is introduced in this paper, which include data flow analysis, transaction flow analysis, system structure analysis and core functions analysis. The prototype system is constructed using .NET, ArcEngine and IDL mixing programming language and its application example are presented. System application results show that this system meets the remote sensing monitoring requirements using greenhouse gases monitoring business applications model to improve the monitoring capability of environmental protection department. Copyright© (2013) by the Asian Association on Remote Sensing.

关键词： Systems analysis

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Study on fuzzy semantic controlling for machinery and equipment manufacturing

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2013 2nd International Conference on Manufacture engineering, Quality and Production System, ICMEQP 2013

作者： Sun, Heng Cai, Shu Bin Joseph Massawe, Richard Happson Chen, Ling Department of Computer Science Jinan University Guangzhou 510632 China Software Engineering Department Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China International School Jinan University Guangzhou 510632 China Jinan University Guangzhou 510632 China

ISBN: (纸本)9783037856970

Machinery and equipment descriptions play an important role in the design and manufacturing of industrial machinery devices and help reducing the design time and manufacturing costs of machinery devices. However, one of the main obstacles to realize efficient device design and manufacturing is the lack of effective semantic description method because of the surprisingly increasing volume and semantically fuzzy natures of the industrial device descriptions. To overcome this problem, this paper presents a novel fuzzy ontology-based device description method and implements the intelligent device retrieval and representation system based on the fuzzy ontology. The fuzzy inference and semantic fusion mechanisms of this approach are demonstrated. © (2013) Trans Tech Publications, Switzerland.

关键词： Machinery

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On charactering of information propagation in online social networks

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Journal of Networks 2013年第1期8卷 124-131页

作者： Han, Xiaoting Niu, Li School of Economics and Management Beihang University Beijing China Key Laboratory of Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Information Resource Management Renmin University of China Beijing China

Recent years have witnessed the explosive growth of online social networks (OSNs), which provide a perfect platform for observing the information propagation. Based on the theory of complex network analysis, considering each node in OSNs as an agent, an information propagation model called IP-OSN has been proposed in this paper, and numerical simulation experiments have been extensively conducted, which show the mechanism of information propagation in OSNs. It can be seen from the experimental results that along with the information spreading scope will be larger while time passing. Moreover, from the network structure perspective, some interesting findings are got. First, the number of initial known nodes has a certain impact on the information propagation speed;however it doesn't affect the number of final known and unknown nodes. Then, the number of neighbors has a great impact on the information propagation process and results. Finally, percentage of different user type is the decisive factor for information propagation either in final node number or propagation speed. This paper attempts to complement the theoretical framework of information propagation and complex networks, and thus to further promote the practice of information control in OSNs. © 2013 ACADEMY PUBLISHER.

关键词： Social networking (online)

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Summarizing Large-Scale database Schema Using Community Detection

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Journal of Computer Science & Technology 2012年第3期27卷 515-526页

作者：王雪周烜王珊 School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China

Schema summarization on large-scale databases is a challenge. In a typical large database schema, a great proportion of the tables are closely connected through a few high degree tables. It is thus difficult to separate these tables into clusters that represent different topics. Moreover, as a schema can be very big, the schema summary needs to be structured into multiple levels, to further improve the usability. In this paper, we introduce a new schema summarization approach utilizing the techniques of community detection in social networks. Our approach contains three steps. First, we use a community detection algorithm to divide a database schema into subject groups, each representing a specific subject. Second, we cluster the subject groups into abstract domains to form a multi-level navigation structure. Third, we discover representative tables in each cluster to label the schema summary. We evaluate our approach on Freebase, a real world large-scale database. The results show that our approach can identify subject groups precisely. The generated abstract schema layers are very helpful for users to explore database.

关键词： schema summarization large scale community detection

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Cancer classification using a local reconstruction and global preserving based semi-supervised dimensionality reduction method

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Journal of Computational Information Systems 2013年第8期9卷 3043-3050页

作者： Cai, Xianfa Wei, Jia Wen, Guihua Li, Jie School of Medical Information Engineering Guangdong Pharmaceutical University Guangzhou 510006 China School of Computer Science and Engineering South China University of Technology Guangzhou 510006 China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055 China

Accurate classification of gene expression data offers great value in understanding the mechanism of tumor and effective clinical treatment. However, in real-world application, people often face a large number of unlabeled samples and meager labeled ones, so semi-supervised learning is applied in cancer classification. In this paper, a Local Reconstruction and Global Preserving Based Semi-Supervised Dimensionality(LRGPSSDR) Method was proposed for cancer classification. LRGPSSDR makes full use of side information, which can set the edge weights of neighborhood graph through minimizing the local reconstruction error and can preserve the global geometric structure of the sampled data set as well as preserving its local geometric structure. Experimental results on five public gene expression datasets show the superior performance of the method.

关键词： Classification (of information)

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