Abstract:Most of the existing semi-supervised clustering algorithms depend on pairwise constraints, and they usually use lots of priori knowledge to improve their accuracies. In this paper, we use another semi-supervised method called label propagation to show how labeled objects help the algorithms to detect clusters. We propose two new semi-supervised algorithms which have the ability to discover clusters of diverse density and arbitrary shape, named MST-based Semi-Supervised clustering using K-labeled objects ( K-SSMST ) and MST-based Semi-Supervised clustering using M-labeled objects ( M-SSMST ). Based on minimum spanning tree ( K-MST ), the two algorithms assign objects to clusters by using labeled objects. K-SSMST algorithm could automatically find natural clusters in a dataset. It does not need any input parameter and only requires K labeled data objects where K is the number of clusters. M-SSMST can detect new clusters when the number of labeled data M is less than K. It only requires one input parameter. Our algorithms were tested on both various artificial datasets and UCI datasets. The results demonstrate the accuracy when compared with other supervised and semi-supervised approaches.

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	1. MST-based Semi-supervised Clustering using M-lableed objects
	HUO Mengmeng,LIU Yangyang,CHEN Xiaoyun
	Computer Science and Technology 30 March 2012
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	Abstract:Most of the existing semi-supervised clustering algorithms depend on pairwise constraints, and they usually use lots of priori knowledge to improve their accuracies. In this paper, we use another semi-supervised method called label propagation to show how labeled objects help the algorithms to detect clusters. We propose two new semi-supervised algorithms which have the ability to discover clusters of diverse density and arbitrary shape, named MST-based Semi-Supervised clustering using K-labeled objects ( K-SSMST ) and MST-based Semi-Supervised clustering using M-labeled objects ( M-SSMST ). Based on minimum spanning tree ( K-MST ), the two algorithms assign objects to clusters by using labeled objects. K-SSMST algorithm could automatically find natural clusters in a dataset. It does not need any input parameter and only requires K labeled data objects where K is the number of clusters. M-SSMST can detect new clusters when the number of labeled data M is less than K. It only requires one input parameter. Our algorithms were tested on both various artificial datasets and UCI datasets. The results demonstrate the accuracy when compared with other supervised and semi-supervised approaches.
	TO cite this article:HUO Mengmeng,LIU Yangyang,CHEN Xiaoyun. MST-based Semi-supervised Clustering using M-lableed objects[OL].[30 March 2012] http://en.paper.edu.cn/en_releasepaper/content/4473656


	2. Public Communication Based on Russian CardsProtocol: a Case Study
	Jia He
	Computer Science and Technology 29 February 2012
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	Abstract:This paper is concerned with public communication with the RussianCards protocol. First, a couple of small flaws in arecorrected. Then an improved Russian Cards protocol is presented. Asa case study, $R(6,31)$(6 players and 31 cards) protocol is used togenerate a common password for 5 parties who wish to access a shared file over the Internet.
	TO cite this article:Jia He. Public Communication Based on Russian CardsProtocol: a Case Study[OL].[29 February 2012] http://en.paper.edu.cn/en_releasepaper/content/4463793

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	3. ESHMP: A Stall-Time-Based Scheduling for Performance Heterogeneous Multicore Systems
	Nie Pengcheng,Duan Zhenhua
	Computer Science and Technology 18 February 2012
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	Abstract:Performance heterogeneous multicore processors (HMP for short), whichconsist of multiple cores with the same instruction set but different performance characteristics (e.g., clock speed, issue width), are of great concern for their ability to deliver higher performance per watt and area for programs with diverse architectural requirements than comparable homogeneous ones. However, such power and area efficiencies of performance heterogeneous multicore systems can only be achieved when workloads are emph{matched} with cores according to the properties of the workload and features of the core.In this paper, we propose a new metric, ASTPI (Average Stall Time per Instruction), to measure the efficiencies of threads in using fast cores. We design, implement and evaluate a new online monitoring approach called ESHMP, which is based on the metric. Our evaluation in the Linux 2.6.21 operating system shows that ESHMP delivers scalability while adapting to a wide variety of applications. Also, our experiment results show that among HMP systems in which heterogeneity-aware schedulers are adopted and there are more than one LLC (Last Level Cache), the architectures where heterogeneous cores share LLCs gain better performance than the ones where homogeneous cores share LLCs.
	TO cite this article:Nie Pengcheng,Duan Zhenhua. ESHMP: A Stall-Time-Based Scheduling for Performance Heterogeneous Multicore Systems[OL].[18 February 2012] http://en.paper.edu.cn/en_releasepaper/content/4463796


	4. Re-formulating Metadata for Privacy-aware Access Control in Information Sharing
	Liu Yimin,Wang Zhihui, Wang Wei, Li Qiuhong
	Computer Science and Technology 10 February 2012
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	Abstract:With the extensive use of XML technology in data transmission and sharing, access control for sensitive and private XML data becomes one of the urgent problems. This paper has proposed an approach based on the minimum secure access tree, which reconstructs the purpose-based metadata model and thus effectively implements privacy-aware data access control. In the approach, the metadata model of purpose is a purpose-based secure access trees, which can be further broken to a group of path expression of xpath {/,//,[ ]} fragments pointing to a set of privacy nodes in the tree. By removing the redundant paths and reducing the number of data nodes, this paper can describe the purpose-based access control policy with the minimum secure access tree. Based on the idea of the xpath fragments query containing, this paper has furthermore presented the algorithms for generating purpose-based minimum secure access tree and implementing privacy-aware data access control mechanism for XML data. The experimental results show that the approach can prevent well the leakage of private XML data, and the query time mainly depends on the structural complexity of query xpath {/,//,[ ]} and the number of nodes on the query path.
	TO cite this article:Liu Yimin,Wang Zhihui, Wang Wei, et al. Re-formulating Metadata for Privacy-aware Access Control in Information Sharing[OL].[10 February 2012] http://en.paper.edu.cn/en_releasepaper/content/4464890


	5. A GPU-Based Parallel Algorithm for Design Structure Matrix (DSM) Partition
	Jing Yuxin,Huang Yu,Shikun Zhang,Cui Weilong
	Computer Science and Technology 08 February 2012
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	Abstract:In complicated system manufacturing and designing, the DSM has been proved to be powerful and effective for analyzing and optimizing the executional order of tasks. Many algorithms have been proposed to optimize the DSM, however, with the system complexity increasing, the number of tasks involved enlarges, which results in the rapid growth of time cost in the algorithms. In this paper, we propose a parallel algorithm using GPU to calculate the DSM Partition, and compare with other algorithm which shows the time cost greatly reduced.
	TO cite this article:Jing Yuxin,Huang Yu,Shikun Zhang, et al. A GPU-Based Parallel Algorithm for Design Structure Matrix (DSM) Partition[OL].[ 8 February 2012] http://en.paper.edu.cn/en_releasepaper/content/4462744


	6. A Graph-Based Conflict-Aware Load-Balancing Algorithm for Database Replication
	Zheng Angen,Liao Jianxin,Wang Jing,Zhu Xiaomin
	Computer Science and Technology 25 December 2011
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	Abstract:In this paper, we present a novel graph-based conflict-aware load-balancing algorithm: GBCA (Graph-Based Conflict-Aware) for certification-based database replication protocols to increase the concurrency and reduce the aborts due to the lack of synchronization during transaction executions. GBCA represents all concurrent transactions in the system and their conflict relationship using a graph, where transactions are represented by nodes and transaction conflicts are represented by edges connecting the inter-conflicting transactions. Node weights account for the complexity of transactions, while edge weights account for the odds of conflicting between different transaction types. We then apply a graph partitioning algorithm to splits this graph into k(the number of replicas) disjoin subsets such that the sum of the edge-weights spanning subsets, called edge-cut, is minimized, while subjecting to the constraint that the sum of the vertex-weights in each subset is balanced and that the virtual nodes (Each database server is represented as a virtual node) are splits into k distinct subsets. Thus, each subset has a unique virtual node which indicates the replica that the transactions of this subset should be assigned to. This graph operation approximates minimizing the number of inter-conflicting transaction executing on different replicas while balancing the load evenly across replicas. At each replica, we adopt a conflict-aware load control technique to avoid data contention thrashing casued by the concentration of inter-conflicting transactions to a single node.
	TO cite this article:Zheng Angen,Liao Jianxin,Wang Jing, et al. A Graph-Based Conflict-Aware Load-Balancing Algorithm for Database Replication[OL].[25 December 2011] http://en.paper.edu.cn/en_releasepaper/content/4455344


	7. Detection of High-risk Zones and Potential Infected Neighbors from Infectious Disease Monitoring Data
	TAN Biying,DUAN Lei,GOU Chi,HUANG Shuyang,FANG Yuhao,ZHAO Xing,TANG Changjie
	Computer Science and Technology 23 December 2011
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	Abstract:Detecting the high-risk zones as well as potential infected geographical neighbor is necessary and important to reduce the loss caused by infectious disease. However, it is a challenging work, since the outbreak of infectious disease is uncertain and unclear. Moreover, the detection should be efficient otherwise the best control and prevention time may be missed. To deal with this problem, we propose a geography high-risk zones detection method by capturing the significant change in the infectious disease monitoring data. The main contribution of this paper includes: (1) Analyzing the challenges of the early warning and detection of infectious disease outbreak; (2) Proposing a method to detect the zone that the number of monitoring cases changes significantly; (3) Defining the infection perturbation to describe the infection probability between two zones; (4) Designing an algorithm to measure the infection perturbation of infectious disease between adjacent zones; (5) Performing extensive experiments on both real-world data and synthetic data to demonstrate the effectiveness and efficiency of the proposed methods.
	TO cite this article:TAN Biying,DUAN Lei,GOU Chi, et al. Detection of High-risk Zones and Potential Infected Neighbors from Infectious Disease Monitoring Data[OL].[23 December 2011] http://en.paper.edu.cn/en_releasepaper/content/4457230


	8. MCCI: Mining Compact Contrast Inequality with Preferred Functions
	DUAN Lei,TANG Changjie,ZUO Jie,ZHANG Tianqing
	Computer Science and Technology 23 December 2011
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	Abstract:Contrast inequality is a new analysis tool to describe the contrast relationship between classes of data in the form of inequality. A Gene Expression Programming (GEP) based method has been proposed for contrast inequality mining in previous work. However, the method does not consider the comprehensibility and clarity of the discovered contrast inequality. The main contributions of this paper include: (1) introducing a compactness measure for contrast inequality, (2) designing a method, named MCCI, to discover compact contrast inequalities with preferred functions, (3) discussing some strategies used in MCCI to keep the compactness measure efficient, and (4) giving an extensive performance study on several data sets from UCI Machine Learning Repository. The experimental results show that MCCI is effective for mining compact contrast inequalities with high discriminative power. And domain knowledge can be introduced in MCCI to evolve inequalities containing preferred functions.
	TO cite this article:DUAN Lei,TANG Changjie,ZUO Jie, et al. MCCI: Mining Compact Contrast Inequality with Preferred Functions[OL].[23 December 2011] http://en.paper.edu.cn/en_releasepaper/content/4457190


	9. Leverage Network Structure for Incremental Document Clustering
	QIAN Tieyun,SI Jianfeng,LI Qing
	Computer Science and Technology 22 December 2011
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	Abstract:Recent studies have shown that link-based clustering methods can significantly improve the performance of content-based clustering. However, most previous algorithms are developed for fixed data sets, and are not applicable to the dynamic environments such as data warehouse and online digital library. In this paper, we introduce a novel approach which leverages the network structure for incremental clustering. Under this framework, both the link and content information are incorporated to determine the host cluster of a new document. The combination of two types of information ensures a promising performance of the clustering results. Furthermore, the status of core members is used to quickly determine whether to split or merge a new cluster. This filtering process eliminates the unnecessary and time-consuming checks of textual similarity on the whole corpus, and thus greatly speeds up the entire procedure. We evaluate our proposed approach on several real-world publication data sets and conduct an extensive comparison with both the classic content based and the recent link based algorithms. The experimental results demonstrate the effectiveness and efficiency of our method.
	TO cite this article:QIAN Tieyun,SI Jianfeng,LI Qing. Leverage Network Structure for Incremental Document Clustering[OL].[22 December 2011] http://en.paper.edu.cn/en_releasepaper/content/4457165


	10. Model-checking of Linear-Time Properties in possibilistic Kripke structure
	LI Lijun,LI Yongming
	Computer Science and Technology 14 November 2011
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	Abstract:Firstly, in this paper, we study the Linear Temporal Logic (LTL) model-checking of linear-time properties in possibilistic Kripke structure. Secondly, we introduce the expression of the safety property and regular property in possibilistic Kripke structure, then give some calculation method related to the above Linear-time properties. Finally , we thoroughly study the verification of safety property and omega regular property using automata.
	TO cite this article:LI Lijun,LI Yongming. Model-checking of Linear-Time Properties in possibilistic Kripke structure[OL].[14 November 2011] http://en.paper.edu.cn/en_releasepaper/content/4449957

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