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Improving performance by creating a native join-index for OLAP

Frontiers of Computer Science 2011年第2期5卷 236-249页

作者： Yansong ZHANG Shan WANG Jiaheng LU National Survey Research Center at Renmin University of China Beijing 100872 China Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

The performance of online analytical processing （OLAP） is critical for meeting the increasing requirements of massive volume analytical applications. Typical techniques, such as in-memory processing, column-storage, and join indexes focus on high perfor- mance storage media, efficient storage models, and reduced query processing. While they effectively perform OLAP applications, there is a vital limitation： main- memory database based OLAP （MMOLAP） cannot provide high performance for a large size data set. In this paper, we propose a novel memory dimension table model, in which the primary keys of the dimension table can be directly mapped to dimensional tuple addresses. To achieve higher performance of dimensional tuple access, we optimize our storage model for dimension tables based on OLAP query workload features. We present directly dimensional tuple accessing （DDTA） based join （DDTA- JOIN）, a technique to optimize query processing on the memory dimension table by direct dimensional tuple access. We also contribute by proposing an optimization of the predicate tree to shorten predicate operation length by pruning useless predicate processing. Our experimental results show that the DDTA-JOIN algorithm is superior to both simulated row-store main memory query processing and the open-source column-store main memory database MonetDB, thanks to the reduced join cost and simple yet efficient query processing.

关键词： directly dimensional tuple accessing (DDTA) – DDTA JOIN – native join index – predicate tree

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Using New Fusion Operations to Improve Trust Expressiveness of Subjective Logic

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Wuhan University Journal of Natural Sciences 2011年第5期16卷 376-382页

作者： ZHOU Hongwei1,2,3,SHI Wenchang1,2,LIANG Zhaohui1,2,LIANG Bin1,2 1.key laboratory of data engineering and knowledge engineering,ministry of education,Beijing 100872,China 2.School of Information,Renmin University of China,Beijing 100872,China 3.Institute of Electronic Technology,Information engineering University of PLA,Zhengzhou 450004,Henan,China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing China School of Information Renmin University of China Beijing China Institute of Electronic Technology Information Engineering University of PLA Zhengzhou Henan China

Subjective logic provides a means to describe the trust relationship of the realworld. However, existing fusion operations it offers Weal fused opiniotts equally, which makes it impossible to deal with the weighted opinions effectively. A. Jcsang presents a solution, which combines the discounting operator and the fusion operator to produce the consensus to the problem. In this paper, we prove that this approach is unsuitable to deal with the weighted opinions because it increases the uncertainty of the consensus. To address the problem, we propose two novel fusion operators that are capable of fusing opinions according to the weight of opinion in a fair way, and one of the strengths of them is improving the trust expressiveness of subjective logic. Furthermore, we present the justification on their definitions with the mapping between the evidence space and the opinion space. Comparisons between existing operators and the ones we proposed show the effectiveness of our new fusion operations.

关键词： trust subjective logic opinion fusion weizht

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A neural network based forecasting method for the unemployment rate prediction using the search engine query data

A neural network based forecasting method for the unemployme...

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2011 8th IEEE International Conference on e-Business engineering, ICEBE 2011

作者： Xu, Wei Zheng, Tingting Li, Ziang Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9780769545189

Unemployment rate prediction has become critically important, because it can help government to make decision and design policies. In recent years, forecast of unemployment rate attracts much attention from governments, organizations, and research institutes, and researchers. Recently, a novel method using search engine query data to forecast unemployment was proposed by scholars. In this paper, a data mining based framework using web information is introduced for unemployment rate prediction. Under the framework, a neural network method, as one of the most effective data mining tools, is developed to forecast unemployment trend using search engine query data. In the proposed method, search engine query data related with employment activities is firstly found. Secondly, feature selection models including correlation coefficient method and genetic algorithm are constructed to reduce the dimension of the query data. Thirdly, various neural networks are employed to model the relationship between unemployment rate data and query data. Fourthly, an optimal neural network is selected as the selective predictor by using the cross-validation method. Finally, the selective neural network predictor with the best feature subset is used to forecast unemployment trend. The empirical results show that the proposed method clearly outperforms the classical forecasting approaches for the unemployment rate prediction. These findings imply that data mining method, such as neural networks, together with web information, can be used as an alternative tool to forecast social/economic hotspot. © 2011 IEEE.

关键词： Forecasting

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Large scale report generation in data consolidation environments of banks

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2012年第SUPPL.1期40卷 5-8页

作者： Qin, Xiongpai Zhou, Xiaoyun Wu, Zhongxin Yang, Hongzhi Wang, Wei Ministry of Education Key Lab of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China Information School Renmin University of China Beijing 100872 China Computer Science Department Jiangsu Normal University Xuzhou 221116 Jiangsu China Beijing Nantian Software Co. Ltd. Beijing 100085 China

To generate large number of reports in a limited time window, four techniques were proposed, including ROLAP&SQL, Shared Scanning, Hadoop based Solution, and MOLAP&Cube Sharding, an algorithm that performs in memory aggregation was designed for the second solution. The experiment results show that all techniques except ROLAP&SQL can meet the time window constraint, the Hadoop based solution is a promising technique owe to its highly scalability. Considering maturity of the techniques and their performance, we put MOLAP&Cube Sharding into practice while keeping an eye on Hadoop for future adoption.

关键词： Custom report data consolidation Hadoop Large bank MOLAP ROLAP

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Probabilistic range queries for Uncertain Trajectories on road networks 11

Probabilistic range queries for Uncertain Trajectories on ro...

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14th International Conference on Extending database Technology: Advances in database Technology, EDBT 2011

作者： Zheng, Kai Trajcevski, Goce Zhou, Xiaofang Scheuermann, Peter School of ITEE University of Queensland Australia Department of EECS Northwestern University United States School of Information Renmin University of China Key Lab. of Data Engineering and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9781450305280

Trajectories representing the motion of moving objects are typically obtained via location sampling, e.g. using GPS or road-side sensors, at discrete time-instants. In-between consecutive samples, nothing is known about the whereabouts of a given moving object. Various models have been proposed (e.g., sheared cylinders;spacetime prisms) to represent the uncertainty of the moving objects both in unconstrained Euclidian space, as well as road networks. In this paper, we focus on representing the uncertainty of the objects moving along road networks as time-dependent probability distribution functions, assuming availability of a maximal speed on each road segment. For these settings, we introduce a novel indexing mechanism - UTH (Uncertain Trajectories Hierarchy), based upon which efficient algorithms for processing spatio-temporal range queries are proposed. We also present experimental results that demonstrate the benefits of our proposed methodologies.

关键词： Trajectories

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Visual group identification method of technical competitors using LinLog graph clustering algorithm

Visual group identification method of technical competitors ...

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IEEE International Conference on Computer Science and Automation engineering

作者： Han, Hong-Qi An, Xiaomi Zhu, Donghua Wang, Xuefeng Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Management and Economics Beijing Institute of Technology Beijing 100872 China

ISBN: (纸本)9781424487257

Visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor groups. Common visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters, and their analysis results may provide misleading information. A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor groups. In the model, technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields, and two competitors have a link when they have high similarity value;LinLog algorithm, which is aimed at producing better clusters, was employed to layout graph with competitors as nodes, their links as edges and technology similarity values as weights of edges. Experiment results show the efficiency of presented method. © 2011 IEEE.

关键词： Visualization

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B-IRP: An improving integrity report protocol for remote attestation

B-IRP: An improving integrity report protocol for remote att...

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International Conference on Communications and Mobile Computing

作者： Zhou, HongWei Yuan, JinHui Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing China School of Information Renmin University of China Beijing China Institute of Electronic Technology Zhengzhou Information Engineering University of China Zhengzhou China

ISBN: (纸本)9780769543574

Trusted platform module (TPM) has little computation capability, and it is the performance bottleneck of remote attestation. In the scenario where the server is the attestation-busy entity which answers attestation requirement frequently, the massive delay is inevitable. Without the modification to TPM, we propose Batch Integrity Report Protocol (BIRP) to overcome the performance bottleneck. B-IRP bundles these requirements in interval as a batch requirement, and creates the response messages for these requirements with one expensive TPM operation. Discussion shows that B-IRP has improved the performance without loss of security. © 2011 IEEE.

关键词： Trusted computing

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Formal analysis of trusted computing: One case study

Formal analysis of trusted computing: One case study

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International Conference on Communications and Mobile Computing

ISBN: (纸本)9780769543574

LS2 is the logic to reason about the property of trusted computing. However, it lacks the capability of modeling the isolation provided by virtualization which is often involved in previous trusted computing system. With the support of changed LS2, we model three types of isolation. Moreover, we formally analyze the integrity measurement property of Trust Visor proposed recently which provides the isolated execution environment for security-sensitive code. © 2011 IEEE.

关键词： Virtualization

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Discovering Chinese compound term using termhood and unithood measures

Proceedings - 2011 6th Annual ChinaGrid Conference, ChinaGri...

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Proceedings - 2011 6th Annual ChinaGrid Conference, ChinaGrid 2011 2011年 60-67页

作者： Kang, Jingjing Liu, Tao Hu, He Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China

ISBN: (纸本)9780769544724

Domain terms play a crucial role in many research areas, which has led to a rise in demand for automatic domain terms extraction. In this paper, we present a two-level evaluation approach based on term hood and unit hood to extract Chinese domain compound terms automatically, which takes the character-level and word-level information into account. To achieve this, we incorporate semantic features by using the word segmentation to recognize single word terms, then leverage the improved C-value and heuristic methods such as word formation pattern and word formation power to evaluate candidates at both levels. By validating our approach with several existing dictionaries, a significant improvement of compound terms detection is achieved. Experiments in legal corpus show our method is superior over other compared methods. © 2011 IEEE.

关键词： Heuristic methods

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K-nearest neighbors in uncertain graph

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第10期48卷 1850-1858页

作者： Zhang, Yinglong Li, Cuiping Chen, Hong Du, Lingxia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Computer and Information Engineer Jiangxi Agriculture University Nanchang 330045 China

In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filtering, fraud detection, and link prediction in social networks etc, rely on efficiently answering k-nearest neighbor queries (kNN), which is the problem of computing the most "similar" k nodes to a given query node. To solve the problem, in this paper a novel method based on measurement of SimRank is proposed. However, because graphs evolve over time and are uncertainly, the computing cost can be very high in practice to solve the problem using the existing algorithms of SimRank. So the paper presents an optimization algorithm. Introducing path threshold, which is suitable in both determined graph and uncertain graph, the algorithm merely considers the local neighborhood of a given query node instead of whole graph to prune the search space. To further improving efficiency, the algorithm adopts sample technology in uncertain graph. At the same time, theory and experiments interpret and verify that the optimization algorithm is efficient and effective.

关键词： Collaborative filtering

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