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14th International Conference on Web-Age Information Management, WAIM 2013

作者： Mo, Shangfeng Chen, Hong Zhang, Xiaoying Li, Cuiping Key Laboratory of Data Engineering and Knowledge Engineering of MOE Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Hunan University of Science and Technology Xiangtan 411201 China

ISBN: (纸本)9783642385612

Wireless Sensor Networks (WSNs) can be viewed as a new type of distributed databases. data management technology is one of the core technologies of WSNs. In this demo we show a Query Processing system based on TinyOS in WSNs, which is called TinyQP. TinyQP provides the in-network processing of several complex queries including real time query, historical query, event detection, aggregate query, top-k query, etc. TinyQP displays the network topology in a graphical way. TinyQP allows the user to remotely execute query commands and browse query result. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Query processing

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MapReduce-Based SimRank Computation and Its Application in Social Recommender System

MapReduce-Based SimRank Computation and Its Application in S...

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IEEE International Conference on Services Economics (SE)

作者： Lina Li Cuiping Li Hong Chen Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China

Recently there has been a lot of interest in graph-based analysis, with examples including social network analysis, recommendation systems, document classification and clustering, and so on. A graph is an abstraction that naturally captures data objects as well as relationships among those objects. Objects are represented as nodes and relationships are represented as edges in the graph. There are many cases in which similarities among nodes are required to compute. SimRank is one of the simple and intuitive algorithms for this purpose. It is rigidly based on the random walk theorem. Existing methods on SimRank computation suffer from one limitation: the computing cost can be very high in practice. In order to optimize the computation of SimRank, a few techniques have been proposed. However, the performance of these methods are still limited by the processing ability of the single computer. Ideally, we would like to develop new parallel solutions that can offer improved processing power to compute SimRank on large data set. In this paper, we propose parallel algorithms for SimRank computation on Map-Reduce framework, and more specifically its open source implementation, Hadoop. Two different parallel methods are proposed and their performances are evaluated and compared. Furthermore, we employ the proposed methods to do the similarity computation in order to recommend appropriate products to users in social recommender systems.

关键词： Computers Iterative methods Recommender systems Computational modeling Parallel processing Equations Sorting

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A new BP algorithm for network marketing performance evaluation of agricultural products

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Journal of Applied Sciences 2013年第20期13卷 4332-4335页

作者： Zou, Chun-Fang Huang, Li-Juan School of of Business Administration Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China School of Information Technology Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China

Network marketing performance evaluation can sum up and improve the network marketing activities for network enterprises. So, how to evaluate network marketing performance has become a matter of concern in the field related. The study mainly takes agricultural products for example and presents a new algorithm for evaluating network marketing performance based on improved BP neural network algorithm. First, a evaluation indicator system for evaluating network marketing performance of agricultural products is constructed;Second the study analyzes the reasons of the defects of BP neural network algorithm and then designs a new BP algorithm and improves it through changing its learning rate to speed up the calculation and simplify the structure of the original BP algorithm;Finally, the improved algorithm is realized with three e_commerce enterprises are taken for examples to evaluate the network marketing performance and verify the validity and feasibility of the model and the experimental results show that the model can evaluate the network marketing performance of different enterprises practically. © 2013 Asian Network for Scientific Information.

关键词： Agricultural products

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Classification model with subspace data-dependent balls

Classification model with subspace data-dependent balls

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International Joint Conference on Computer Science and Software engineering (JCSSE)

作者： Nattapon Klakhaeng Thanapat Kangkachit Thanawin Rakthanmanon Kitsana Waiyamai Data Analysis and Knowledge Discovery Laboratory Department of Computer Engineering Faculty of Engineering Kasetsart University Bangkok Thailand

ISBN: (纸本)9781479908059

data-Dependent Ball (DDB) is a pre-processing algorithm that transforms quantitative into binary data by mapping them into a set of balls. In datasets with large number of dimensions, data-dependent balls are less significant due to the distance calculation in the mapping process. To reduce number of ball dimensions, this paper proposes a method for subspace data-dependent balls (SDDB) generation. SDDB starts by ranking features using information gain, and then eliminating input features based on ratio r. Subspace data-dependent balls are then created and filtered out with respect to their size and purity. Finally, a C4.5 decision tree classification model is constructed using subspace data-dependent balls as features. Experimental results from 8 TICI datasets show that the accuracy from a combination of SDDB and C4.5 is better than the combination of DDB and C4.5 in terms of accuracy.

关键词： Accuracy Decision trees Training Classification algorithms Transforms Glass Ionosphere

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Apriori Gene Set-based Microarray Analysis for Disease Classification Using Unlabeled data

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Procedia Computer Science 2013年 23卷 137-145页

作者： Worrawat Engchuan Jonathan Hoyin Chan Data and Knowledge Engineering Laboratory (D-Lab) School of Information Technology King Mongkut's University of Technology Thonburi Bangkok Thailand 10140

Gene set-based microarray analysis allows researchers to better analyze the gene expression data for studying complex diseases like cancer. By transforming gene expression data into another form using gene set information, the biomarkers will have higher discriminative power and should result in more accurate disease classification. This work compares two techniques for applying our previously developed NCFS-i-based method to deal with unlabeled data, i.e. to make predictive diagnosis. Seven cancer datasets that include 4 breast cancer and 3 lung cancer datasets were used in this study. The results show that inferring gene set activity using curated phenotype-correlated genes (PCOGs) sets of training data is a more robust method for applying NCFS-i- based method to work with unlabeled data, providing biologically relevant gene sets.

关键词： gene set activity gene expression microarray analysis cancer classification feature selection

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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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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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A broadcasting multiple blind signature scheme based on quantum GHZ entanglement

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International Journal of Modern Physics: Conference Series 2014年第33期ijmpcs卷

作者： Yuan Tian Hong Chen Yan Gao Honglin Zhuang Haigang Lian Zhengping Han Peng Yu Xiangze Kong Xiaojun Wen Key Laboratory of Data Engineering and Knowledge Engineering China (Remin University of China) of Ministry of Education Beijing 100872 China School of Information Renmin University of China Beijing 100872 China China Computer User Association Information Protection Branch Beijing 100089 China School of Computer Science and Engineering Beihang University Beijing 100083 China School of Electronics & Information Engineering Shenzhen Polytechnic Shenzhen 518055 China

Using the correlation of the GHZ triplet states, a broadcasting multiple blind signature scheme is proposed. Different from classical multiple signature and current quantum signature schemes, which could only deliver either multiple signature or unconditional security, our scheme guarantees both by adopting quantum key preparation, quantum encryption algorithm and quantum entanglement. Our proposed scheme has the properties of multiple signature, blindness, non-disavowal, non-forgery and traceability. To the best of our knowledge, we are the first to propose the broadcasting multiple blind signature of quantum cryptography.

关键词： Broadcasting multiple blind signature quantum encryption algorithm quantum entanglement quantum cryptography

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