基于PrefixSpan的快速交互序列模式挖掘算法

为了克服序列模式挖掘过程中重复运行挖掘算法而产生的时空消耗,提出了一个快速、简单而有效序列模式的交互式算法FISPM,利用前次挖掘得到的序列构造序列模式数据库用来存储挖掘出来的所有序列, 通过缩减本次挖掘所要构造投影数据库的频繁项的数量来减少构造投影数据库所需的时间以及投影数据库的大小,从而减少时间和空间消耗,提高挖掘效率.通过设置全局最小支持度来减少算法迭代次数. 实验结果证明在交互挖掘过程中FISPM效率优于PrefixSpan.     

A Fast Distributed Algorithm for Association Rule Mining Based on Binary Coding Mapping Relation

Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as ＂and＂, ＂or＂ and ＂xor＂. Applying this idea in the existed distributed association rule mining al gorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.     

Incremental Web Usage Mining Based on Active Ant Colony Clustering

To alleviate the scalability problem caused by the increasing Web using and changing users＇ interests, this paper presents a novel Web Usage Mining algorithm-Incremental Web Usage Mining algorithm based on Active Ant Colony Clustering. Firstly, an active movement strategy about direction selection and speed, different with the positive strategy employed by other Ant Colony Clustering algorithms, is proposed to construct an Active Ant Colony Clustering algorithm, which avoid the idle and ＂flying over the plane＂ moving phenomenon, effectively improve the quality and speed of clustering on large dataset. Then a mechanism of decomposing clusters based on above methods is introduced to form new clusters when users＇ interests change. Empirical studies on a real Web dataset show the active ant colony clustering algorithm has better performance than the previous algorithms, and the incremental approach based on the proposed mechanism can efficiently implement incremental Web usage mining.     

Mining compressed frequent subtrees set

The number of frequent subtrees usually grows exponentially with the tree size because of combinatorial explosion. As a result, there are too many frequent subtrees for users to manage and use. To solve this problem, we generalize a compressed frame based on δ-cluster to the problem of compressing frequent-subtree sets, and propose an algorithm RPTlocal which can mine compressed frequent subtrees set directly. This algorithm sacrifices the theoretical bounds but still has good compression quality. By pruning the search space and generating frequent subtrees directly, this algorithm is also efficient. Experiment result shows the representative subtrees mining by RPTlocal is almost two orders of magnitude less than the whole collection of the closed subtrees, and is more efficient than CMtreeMiner, the algorithm for mining both closed and Maximal frequent subtrees. Foundation item: Supported by the National Natural Science Foundation of China (70371015)     

Solving integer programming by evolutionary soft agent

Many practical problems in commerce and industry involve finding the best way to allocate scarce resources a-mong competing activities. This paper focuses on the problem of integer programming, and describes an evolutionary soft a-gent model to solve it. In proposed model, agent is composed of three components: goal, environment and behavior. Experimental shows the model has the characters of parallel computing and goal driving. Foundation item: Supported by the National Natural Science Foundation of China( 60205007) , Natural Science Foundation of Guangdong Province(001264), Research Foundation of Software Technology Key Laboratory in Guangdong Province and Research Foundation of State Key Laboratory for Novel Software Technology at Nanjing University Biography: Yin Jian ( 1968-), male, Associate professor, research direction: artificial intelligence, data mining.     

Methods of constructing optimal wavelet filters based on genetic algorithm

In this paper, algorithms of constructing wavelet filters based on genetic algorithm are studied with emphasis on how to construct the optimal wavelet filters used to compress a given image,due to efficient coding of the chromosome and the fitness function, and due to the global optimization algorithm, this method turns out to be perfect for the compression of the images. Foundation item: Supported by the Natural Science Foundation of Education of Hunan Province(21010506) Biography: Wen Gao-jin( 1978-), male, Master candidate, research direction: evolutionary computing.     

Testing Forms in Web Applications Automatically

Forms enhance both the dynamic and interactive abilities of Web applications and the system complexity. And it is especially important to test forms completely and thoroughly. Therefore, this paper discusses how to carry out the form testing by different methods in the related testing phases. Namely, at first, automatically abstracting forms in the Web pages by parsing the HTML documents; then, ohtai ning the testing data with a certain strategies, such as by requirement specifications, by mining users＇ hefore input informarion or by recording meehanism; and next executing the testing actions automatically due to the well formed test cases; finally, a case study is given to illustrate the convenient and effective of these methods.     

Time-Based Dynamic Trust Model Using Ant Colony Algorithm

The trust in distributed environment is uncertain, which is variation for various factors. This paper introduces TDTM, a model for time-based dynamic trust. Every entity in the distribute environment is endowed with a trust-vector, which figures the trust intensity between this entity and the others. The trust intensity is dynamic due to the time and the inter-operation between two entities, a method is proposed to quantify this change based on the mind of ant colony algorithm and then an algorithm for the transfer of trust relation is also proposed. Furthermore, this paper analyses the influence to the trust intensity among all entities that is aroused by the change of trust intensity between the two entities, and presents an algorithm to resolve the problem. Finally, we show the process of the trusts＇ change that is aroused by the time＇s lapse and the inter-operation through an instance.     

Stable initialization scheme for K -means clustering

Though K-means is very popular for general clustering, its performance which generally converges to numerous local minima depends highly on initial cluster centers. In this paper a novel initialization scheme to select initial cluster centers for K-means clustering is proposed. This algorithm is based on reverse nearest neighbor (RNN) search which retrieves all points in a given data set whose nearest neighbor is a given query point. The initial cluster centers computed using this methodology are found to be very close to the desired cluster centers for iterative clustering algorithms. This procedure is applicable to clustering algorithms for continuous data. The application of proposed algorithm to K-means clustering algorithm is demonstrated. Experiment is carried out on several popular datasets and the results show the advantages of the proposed method. Foundation item: Supported by the National Natural Science Foundation of China (60503020, 60503033, 60703086), the Natural Science Foundation of Jiangsu Province (BK2006094), the Opening Foundation of Jiangsu Key Laboratory of Computer Information Processing Technology in Soochow University (KJS0714) and the Research Foundation of Nanjing University of Posts and Telecommunications (NY207052, NY207082)     

Binary Sequences from a Pair of Elliptic Curves

A family of binary sequences were constructed by using an elliptic curve and its twisted curves over finite fields. It was shown that these sequences possess ＂good＂ cryptographie properties of 0-1 distribution, long period and large linear complexity. The results indicate that such se quences provide strong potential applications in cryptography.     

Verifiable （ t, n） Threshold Signature Scheme Based on Elliptic Curve

Based on the difficulty of solving the ECDLP (elliptic curve discrete logarithm problem) on the finite field, we present a (t, n) threshold signature scheme and a verifiable key agreement scheme without trusted party. Applying a modified elliptic curve signature equation, we get a more efficient signature scheme than the existing ECDSA (ellipticcurve digital signature algorithm) from the computability and security view. Our scheme has a shorter key, faster computation, and better security.     

A new algorithm for routing in ad-hoc network

In this paper, we propose a new algorithm for wireless mobile and ad-hoc network, which establishes dynamic cluster of nodes. The proposed algorithm, namely, the Mobility Sensitive Routing Protocol (MSRP), consists of routing in cluster and routing between clusters. Ad-hoc network can utilize MSRP to reduce information exchange and communication bandwidth, to shorten route acquisition delay, and to accommodate more nodes. Foundation item: Supported by the National Natural Science Foundation of China (60133010,60073043,70071042). Biography: Zhang Jian (1976-), male, Ph. D candidate. Lecturer, research direction: computer network, network optimization.     

Two-phase genetic algorithm applied in the optimization of multi-modal function

This paper presents a two-phase genetic algorithm (TPGA) based on the multi-parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population’s evolvement to diversity or convergence according to the population size and the crossover size, so we make it run in different forms during the global and local optimization phases and then forms TPGA. The experiment results show that TPGA is very efficient for the optimization of low-dimension multi-modal functions) usually we can obtain all the global optimal solutions. Foundation item: Supported by the National Natural Science Foundation of China (70071042, 60073043,60133010) Biography: Huang Yu-zhen ( 1977-), female, Master candidate, research direction; evolution computation.     

Research on Fault Tolerant Scheduling Algorithms of Web Cluster Based on Probability

Aiming at the soft real time fault tolerant demand of critical web applications at present, such as E-commerce, a new fault tolerant scheduling algorithm based on probability is proposed. ““““““““Ib achieve fault tolerant scheduling, the primary/slave backup technology is applied on the basis of task‘s self similar accessing characteristics, when the primary task completed successfully, the resources allocated for the slave task are reclaimed, thus advancing system‘s efficiency. Experimental results demonstrate on the premise of satisfying system‘s certain fault tolerant probability, task‘s schedulabilistic probability is improved, especially, the higher task‘s self similar degree is, the more obviously the utilization of system resources is enhanced.     

Collaborative Filtering Algorithms Based on Kendall Correlation in Recommender Systems

In this work, Kendall correlation based collaborative filtering algorithms for the recommender systems are proposed. The Kendall correlation method is used to measure the correlation amongst users by means of considering the relative order of the users＇ ratings. Kendall based algorithm is based upon a more general model and thus could be more widely applied in e-commerce. Another discovery of this work is that the consideration of only positive correlated neighbors in prediction, in both Pearson and Kendall algorithms, achieves higher accuracy than the consideration of all neighbors, with only a small loss of coverage.     

A New Mechanism Based on Similar Clouds Watermark for Database＇s Information Security

This paper studies the digit watermark technology of numeric attributes in relational database for database‘s information security. It proposes a new mechanism based on similar clouds watermark and gives the concept of similar clouds. The algorithm SCWA that can insert the meaning wa-termark and detect it from the watermarked data is described. The mechanism can effectively and broadly scatter the watermark in the database; therefore the watermark is very robust.     

Genetic algorithm for Chinese postman problems

Chinese Postman Problem is an unsettled graphic problem. It was approached seldom by evolutionary computation. Now we use genetic algorithm to solve Chinese Postman Problem in undirected graph and get good results. It could be extended to solve Chinese postman problem in directed graph. We make these efforts for exploring in optimizing the mixed Chinese postman problem. Foundation item: Supported by the National Natural Science Foundation of China (60133010, 70071042) Biography: Jiang Hua(1974-), male, Master candidate, research direction: Evolutionary computation.     

A parallel global-local mixed evolutionary algorithm for multimodal function optimization based on domain decomposition

This paper presents a parallel two-level evolutionary algorithm based on domain decomposition for solving function optimization problem containing multiple solutions. By combining the characteristics of the global search and local search in each sub-domain, the former enables individual to draw closer to each optima and keeps the diversity of individuals, while the latter selects local optimal solutions known as latent solutions in sub-domain. In the end, by selecting the global optimal solutions from latent solutions in each sub-domain, we can discover all the optimal solutions easily and quickly. Foundation item: Supported by the National Natural Science Foundation of China (60133010,60073043,70071042) Biography: Wu Zhi-jian(1963-), male, Associate professor, research direction: parallel computing, evolutionary computation.     

Respective roles of short-and long-range interactions in protein folding

A new method was presented to discuss the respective roles of short- and long-range interactions in protein folding. It‘s based on an off-lattice model, which is also being called as toy model. Simulated annealing algorithm was used to search its native conformation. When it is applied to analysis proteins lagt and laho, we find that helical segment catmot fold into native conformation without the influence of long-range interactions. That‘s to say that long-range interactions are the main determinants in protein folding.