45158244
Discovering pattern-based subspace clusters by pattern tree
Traditional clustering models based on distance similarity are not always effective in capturing correlation among data objects, while pattern-based clustering can do well in identifying correlation hidden among data objects. However, the state-of-the-art pattern-based clustering methods are inefficient and provide no metric to measure the clustering quality. This paper presents a new pattern-based subspace clustering method, which can tackle the problems mentioned above. Observing the analogy between mining frequent itemsets and discovering subspace clusters, we apply pattern tree - a structure used in frequent itemsets mining to determining the target subspaces by scanning the database once, which can be done efficiently in large datasets. Furthermore, we introduce a general clustering quality evaluation model to guide the identifying of meaningful clusters. The proposed new method enables the users to set flexibly proper quality-control parameters to meet different needs. Experimental results on synthetic and real datasets show that our method outperforms the existing methods in both efficiency and effectiveness.
27939024
Junction Tree Factored Particle Inference Algorithm for Multi-Agent Dynamic Influence Diagrams
As MMDPs are difficult to represent structural relations among Agents and MAIDs can not model dynamic environment, we present Multi-Agent dynamic influences (MADIDs). MADIDs have stronger knowledge representation ability and MADIDs may efficiently model dynamic environment and structural relations among Agents. Based on the hierarchical decomposition of MADIDs, a junction tree factored particle filter (JFP) algorithm is presented by combing the advantages of the junction trees and particle filter. JFP algorithm converts the distribution of MADIDs into the local factorial form, and the inference is performed by factor particle of propagation on the junction tree. Finally, and the results of algorithm comparison show that the error of JFP algorithm is obviously less than BK algorithm and PF algorithm without the loss of time performance.
22165485
An Efficient Fuzzy Kohonen Clustering Network Algorithm
Fuzzy Kohonen clustering networks (FKCN) are well known for clustering analysis (unsupervised learning and self-organizing). This classification of FKCN algorithm is a set of iterative procedures that suffer some major problems, for example its constringency rate is not too fast for a large amount of datasets. To overcome these defects, an efficient fuzzy Kohonen network algorithm is proposed in this paper, which can significantly reduce the computation time required to partition a dataset into desired clusters. By introducing the threshold values and fuzzy convergence operators in the network learning procedure to adjust the learning rates dynamically, the network convergence rate is greatly improved and the error rates of dataset cluster are significantly decreased. Experimental results show the new algorithm is on average three times faster than the original FKCN algorithm. We also demonstrate that the quality of the improved FKCN is better than the original FKCN algorithm.
8394517
Predicting the Usage of P2P Sharing Software: The Role of Trust and Perceived Risk
Peer-to-Peer, or P2P sharing has gone through fast growth in recent years and drawn the interests of Information Systems (IS) researchers. However, there is a lack of empirical study on the individual's behavior of using P2P sharing software. Given the current existence of various uncertainties in P2P sharing, it is crucial to understand the factors that affect individual's usage of P2P sharing software. In this paper, we develop and empirically test a usage intention model which includes trust in the vendor of P2P sharing software and perceived risk as two major antecedent beliefs to the usage intention. Several trust antecedents are also identified in the model. Our preliminary results show the support for the model, and offer some important implications for software vendors in P2P sharing industry and regulatory bodies.
16691131
Software Productivity Analysis with CSBSG Data Set
The aim is to report on an initial exploratory statistical analysis of the relationship between software productivity and its influencing factors in China. We analyzed of a data set containing project measurement data which were collected from lots of IT companies in China by China Software Benchmarking Standards Group (CSBSG), established by China Software Process Improvement Network (CSPIN), China.Productivity with its influencing factors was investigated using a exploratory statistical analysis. Only 133 closed projects with high ratings could be used in this investigation. Furthermore, confidentiality and data quality, data filling ratio and sizing method were considered as major issues during our current work and also for future investigation. Overall, we observed that influencing factors - project size, project type and business area - do affect productivity with different level statistical significance. However, no clear evidence can be observed that factors, like maximum team size and programming languages affect productivity. Ongoing analysis of productivity and its influencing factors. Based on current productivity analysis results, comparative analysis between counties and estimation modeling will be investigated in future.
33547700
Collaborative and interactive room design on the web
Design on the Web raises challenging questions concerning how users interact with objects, applications, and other users. In this work, we propose a collaborative and interactive client-server design framework and implement a room design system for our study. We have integrated technologies used in distributed computation (Java and CORBA) and computer graphics (VRML). It divides the design process into three tiers. First, collaborative and interactive design, viewing, and publishing. Second, scene generation. Third, scene database management. Our system can be applied in Electronic Commerce to improve the existing systems by allowing customers to select furniture and to visualize the whole furnished room in 3D.
694386
A Data Storage Mechanism for P2P VoD Based on Multi-channel Overlay
It is a big challenge to provide Video-on-Demand streaming services over Internet in a scalable way. Currently, many researchers use a single channel overlay to implement the scalability of on-demand streaming services. However, in a real application environment, various channels in a P2P VOD system have different popularities, which probably cause the imbalance of data storage-capability of the whole system. It results in a problem that a mass of unpopular channels' caching capability can not be used to satisfy the data requirements of the whole system. In order to solve the problem, this paper proposes a new data-storage mechanism, which constructs a multi-channel overlay to optimize the whole system's caching-capability and greatly improves unpopular channel's caching efficiency. The experimental results show that this mechanism can achieve significant effects.