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共 841 条记录，以下是431-440 订阅

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Modeling the locality in graph traversals

Modeling the locality in graph traversals

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41st International Conference on Parallel Processing, ICPP 2012

作者： Yuan, Liang Ding, Chen Štefankovič, Daniel Zhang, Yunquan Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Graduate University of Chinese Academy of Sciences China Computer Science Department University of Rochester United States

ISBN: (纸本)9780769547961

An increasing number of applications in physical and social sciences require the analysis of large graphs. The efficiency of these programs strongly depends on their memory usage especially the locality of graph data access. Intuitively, the locality in computation should reflect the locality in graph topology. Existing locality models, however, operate either at program level for regular loops and arrays or at trace level for arbitrary access streams. They are not sufficient to characterize the relation between locality and connectivity. This paper presents a new metrics called the vertex distance and uses it to model the locality in breadth-first graph traversal (BFS). It shows three models that use the average node degree and the edge distribution to predict the number of BFS levels and the reuse distance distribution of BFS. Finally, it evaluates the new models using random and non-random graphs. © 2012 IEEE.

关键词： Graph theory

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RGH: An efficient RSU-aided group-based hierarchical privacy enhancement protocol for VANETs

RGH: An efficient RSU-aided group-based hierarchical privacy...

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13th International Conference on Web-Age Information Management, WAIM 2012

作者： Yang, Tao Kong, Lingbo Yu, Liangwen Hu, Jianbin Chen, Zhong MoE Key Lab. of High Confidence Software Technologies Peking University 100871 Beijing China MoE Key Lab. of Computer Networks and Information Security Peking University 100871 Beijing China School of Electronics Engineering and Computer Science Peking University 100871 Beijing China School of Software Engineering Beijing Jiaotong University 100044 Beijing China

ISBN: (纸本)9783642322808

VANETs are gaining significant prominence from both academia and industry in recent years. In this paper, we introduce an Efficient RSU-aided Group-based Hierarchical Privacy Enhancement Protocol for VANETs. The protocol exploits the Road-Side-Unit (RSU) to form a temporary group based on the vehicles around it. As the group leader, the RSU takes charge of the verification of the member car through the Revocation List from the DoT (Department of Transportation). The RSU also generates the session key and determines the configuration for the group. The RSU handles the message from the group member, and then sends it to other group members. RSUs have hierarchical security because of the real environment secure threats. RSUs are divided into High-level RSU (HRSU) and Low-level RSU (LRSU). HRSU inserts a message-related trace entry into the trace log while LRSU attaches trace Tag on the message. HRSU has to submit the trace log to the Department of Audit (DoA) by secure way periodically. If required, DoA can trace out the disputed message's real signer with the cooperation of the DoT. Comparison with other existing classic schemes in the literature has been performed to show the efficiency and applicability of our scheme. © 2012 Springer-Verlag.

关键词： Vehicular ad hoc networks

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Business rule engine-based framework for SaaS application development

Business rule engine-based framework for SaaS application de...

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2nd International Conference on Cloud Computing and Services science, CLOSER 2012

作者： Zhang, Xiuwei He, Keqing Wang, Jian Wang, Chong Li, Zheng State Key Lab. of Software Engineering Wuhan University Wuhan China Computer School Wuhan University Wuhan China 94005 Troops of PLA Jiuquan China

ISBN: (纸本)9789898565051

software as a Service (SaaS) is becoming a new direction of software industry in the new cloud computing era. In order to satisfy business policy changes and personalized requirements from different tenants in SaaS applications, business rule management must support multi-tenancy and online customization. This paper proposed a framework based on business rule engine, decoupling of business logic rule from SaaS application, which makes SaaS application more robust and maintainable. It takes business rule as an independent and online maintainable part of SaaS application, which could allow tenants to safely upgrade, delete or create rules during runtime. Finally, a practical case study of absence approval-process in attendance management system evaluates the effectiveness of the framework.

关键词： software as a service (SaaS)

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Tag ranking by propagating relevance over tag and image graphs 12

Tag ranking by propagating relevance over tag and image grap...

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4th International Conference on Internet Multimedia Computing and Service, ICIMCS 2012

作者： Li, Minxian Tang, Jinhui Li, Haojie Zhao, Chunxia School of Computer Science and Technology Nanjing University of Science and Technology Nan Jing China State Key Lab. for Novel Software Technology Nanjing University Nan Jing China School of Software Dalian University of Technology Dalian China

ISBN: (纸本)9781450316002

In this paper, we explore the problem of tag ranking by propagating relevance over community-contributed images and their associated tags. To rank the tags more accurately, we propose a novel tag ranking scheme through a two-stage graph-based relevance propagation approach. The first stage constructs a tag graph on each image and implements a random walk process on it in order to get the initial relevance of each tag for one image and the second stage builds a κNN-sparse image graph and propagates the relevance of tags among the web images. The proposed approach is purely data-driven, since the explicit relevance models between tags and images are not assumed. More importantly, compared to existing tag ranking approaches, we propose to leverage the relevance propagation over two graphs, which take into count not only the relationship among tags but also the relationship among images. Extensive experiments have conducted on the NUS-WIDE dataset have demonstrated the effectiveness of the proposed approach. Copyright © 2012 ACM.

关键词： Graphic methods

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Immune - Difference algorithm

Immune - Difference algorithm

引用

2012 International Conference on computer science and Electronics Engineering, ICCSEE 2012

作者： Fu, Xuan Liu, Hao Fan, Yaoqun Zhao, Xinchao School of Science Beijing University of Posts and Telecommunications Beijing 100876 China State Key Lab. for Novel Software Technology Nanjing University Nanjing 210093 China

ISBN: (纸本)9780769546476

This paper introduces difference mutation idea for diversified search to elitist search-based immune optimization algorithm for function optimization. The idea of difference mutation is merged into the process of clonal selection and hupermutation algorithm, so that the new solutions have the tendency to get close to the global optimal solution. The introduction of differential algorithm idea greatly accelerates the convergence speed and makes the search algorithm produces better performance under a fixed number of steps. In short, the performance of the immune algorithm is greatly improved by introduction of differential algorithm. © 2012 IEEE.

关键词： Evolutionary algorithms

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Mining frequent itemsets using node-sets of a prefix-tree

Mining frequent itemsets using node-sets of a prefix-tree

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23rd International Conference on Database and Expert systems Applications, DEXA 2012

作者： Qu, Jun-Feng Liu, Mengchi State Key Lab. of Software Engineering School of Computer Wuhan University Wuhan 430072 China School of Computer Science Carleton University Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9783642325991

Frequent itemsets are important information about databases, and efficiently mining frequent itemsets is a core problem in data mining area. The divide-and-conquer strategy is very applicable to the problem. Most algorithms adopting the strategy construct a very large number of conditional databases when mining frequent itemsets. Representations of conditional databases and methods of constructing them greatly influence the performance of such algorithms. In this study, we propose a node-set structure for representing a conditional database, and develop a novel node-set-based algorithm, NS, for mining frequent itemsets. During a mining process, all the node-sets derive from a prefix-tree storing the complete frequent itemset information about the mined database. Compared with previous conditional database representations, node-sets are compact and contiguous on which NS can be performed fast. Constructing conditional databases involves counting for items. In NS, the counting procedure and the construction procedure are blended, which saves the time for scanning conditional databases, and further, the major operations of constructing conditional databases are very simple comparisons. Experimental data show that NS outperforms several famous algorithms including FPgrowth* and LCM, ones of the fastest algorithms, for various databases. © 2012 Springer-Verlag.

关键词： Database systems

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A fast algorithm for frequent itemset mining using Patricia* structures

A fast algorithm for frequent itemset mining using Patricia*...

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14th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2012

ISBN: (纸本)9783642325830

Efficient mining of frequent itemsets from a database plays an essential role in many data mining tasks such as association rule mining. Many algorithms use a prefix-tree to represent a database and mine frequent itemsets by constructing recursively conditional prefix-trees from the prefix-tree. A (conditional) prefix-tree can be stored in various structures. The construction and traversal costs of prefix-trees, or rather their storage structures, take a large proportion in the whole cost for such algorithms. The PatriciaMine algorithm employs a Patricia trie to store a prefix-tree and shows good performance. In this study, we introduce an efficient Patricia*structure for storing a prefix-tree. A Patricia*structure is more compact and contiguous than a corresponding Patricia trie, and thus the construction and traversal costs of the former are less than those of the latter. Previous prefix-tree-based algorithms adopt a similar mining procedure, in which most nodes in a prefix-tree are repeatedly accessed when the prefix-tree is processed. The paper presents a novel mining procedure in which node accesses for a prefix-tree are greatly reduced. We propose the PatriciaMine* algorithm that is the combination of the Patricia*structure with the proposed procedure. Experimental data show that PatriciaMine*outperforms not only PatriciaMine but also several fast algorithms, such as FPgrowth*and dEclat, for various databases. © 2012 Springer-Verlag.

关键词： Data mining

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Mining high utility itemsets without candidate generation 12

Mining high utility itemsets without candidate generation

引用

21st ACM International Conference on Information and Knowledge Management, CIKM 2012

作者： Liu, Mengchi Qu, Junfeng State Key Lab. of Software Engineering School of Computer Wuhan University Wuhan 430072 China School of Computer Science Carleton University Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781450311564

High utility itemsets refer to the sets of items with high utility like profit in a database, and efficient mining of high utility itemsets plays a crucial role in many real-life applications and is an important research issue in data mining area. To identify high utility itemsets, most existing algorithms first generate candidate itemsets by overestimating their utilities, and subsequently compute the exact utilities of these candidates. These algorithms incur the problem that a very large number of candidates are generated, but most of the candidates are found out to be not high utility after their exact utilities are computed. In this paper, we propose an algorithm, called HUI-Miner (High Utility Itemset Miner), for high utility itemset mining. HUI-Miner uses a novel structure, called utility-list, to store both the utility information about an itemset and the heuristic information for pruning the search space of HUI-Miner. By avoiding the costly generation and utility computation of numerous candidate itemsets, HUI-Miner can efficiently mine high utility itemsets from the utility-lists constructed from a mined database. We compared HUI-Miner with the state-of-the-art algorithms on various databases, and experimental results show that HUI-Miner outperforms these algorithms in terms of both running time and memory consumption. © 2012 ACM.

关键词： Miners

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Selection methods research based on stochastic ranking for constrained optimization

Selection methods research based on stochastic ranking for c...

引用

2012 International Conference on computer science and Electronics Engineering, ICCSEE 2012

作者： Jiang, Ling Zhao, Wei Li, Bo Qin, Yiwen Zhao, Xinchao School of Science Beijing University of Posts and Telecommunications Beijing 100876 China State Key Lab. for Novel Software Technology Nanjing University Nanjing 210093 China

ISBN: (纸本)9780769546476

This paper describes some general constrained optimization problem-solving methods at first, and then different ideas of combining particle swarm optimization with stochastic ranking are proposed. Accordingly, three algorithms (SR1, SRe1, SRhs) are constructed together with disturbance idea and their pros and cons are analyzed. Finally, some typical benchmarks are used to confirm their performance and achieve better results. © 2012 IEEE.

关键词： Constrained optimization

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Stock market volatility prediction: A service-oriented multi-kernel learning approach

Stock market volatility prediction: A service-oriented multi...

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2012 IEEE 9th International Conference on Services Computing, SCC 2012

作者： Wang, Feng Liu, Ling Dou, Chenxiao State Key Lab. of Software Engineering Wuhan University Wuhan China College of Computing Georgia Institute of Technology Atlanta GA United States School of Computer Science Wuhan University Wuhan China

ISBN: (纸本)9780769547534

Stock market is an important and active part of nowadays financial markets. Stock time series volatility analysis is regarded as one of the most challenging time series forecasting due to the hard-to-predict volatility observed in worldwide stock markets. In this paper we argue that the stock market state is dynamic and invisible but it will be influenced by some visible stock market information. Existing research on financial time series analysis and stock market volatility prediction can be classified into two categories: in depth study of one market factor on the stock market volatility prediction or prediction by combining historical price fluctuations with either trading volume or news. In this paper we present a service-oriented multi-kernel based learning framework (MKL) for stock volatility analysis. Our MKL service framework promotes a two-tier learning architecture. In the top tier, we develop a suite of data preparation and data transformation techniques to provide a source-specific modeling, which transforms and normalizes a source specific input dataset into the MKL ready data representation. Then we apply data alignment techniques to prepare the datasets from multiple information sources based on the classification model we choose for cross-source correlation analysis. In the next tier, we develop model integration methods to perform three analytic tasks: (i) building one sub-kernel per source, (ii) learning and tuning the weights for sub-kernels through weight adjustment methods and (iii) performing multi-kernel based cross-correlation analysis of market volatility. To validate the effectiveness of our service oriented MKL approach, we performed experiments on HKEx 2001 stock market datasets with three important market information sources: historical prices, trading volumes and stock related news articles. Our experiments show that 1) multi-kernel learning method has a higher degree of accuracy and a lower degree of false prediction, compared to exist

关键词： Forecasting

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