Clustering is one of the recently challenging tasks since there is an ever.growing amount of data in scientific research and commercial applications. High quality and fast document clustering algorithms are in great d...Clustering is one of the recently challenging tasks since there is an ever.growing amount of data in scientific research and commercial applications. High quality and fast document clustering algorithms are in great demand to deal with large volume of data. The computational requirements for bringing such growing amount data to a central site for clustering are complex. The proposed algorithm uses optimal centroids for K.Means clustering based on Particle Swarm Optimization(PSO).PSO is used to take advantage of its global search ability to provide optimal centroids which aids in generating more compact clusters with improved accuracy. This proposed methodology utilizes Hadoop and Map Reduce framework which provides distributed storage and analysis to support data intensive distributed applications. Experiments were performed on Reuter's and RCV1 document dataset which shows an improvement in accuracy with reduced execution time.展开更多
In the distributed environment,robots should be able to provide users with adaptive services automatically according to the situational information changing dynamically which is obtained from both users and their envi...In the distributed environment,robots should be able to provide users with adaptive services automatically according to the situational information changing dynamically which is obtained from both users and their environments.The workflow depends on situational information obtained from physical environments and provides context-aware services automatically based on the information retrieved.And the workflow in the business processes and the distributed computing environments have supported the automation of services by connecting tasks.The workflow needs to specify ubiquitous situational information as state-transition constraints.However,the delivery and use of sensor data in the workflow is a difficult problem for the robot system.In order to bridge the gap between applications and low-level constructs and to acquire raw situational information for the execution of the context-aware workflow in the robot systems,this paper presents an approach which can achieve the sensor data transmission between a sensing server and a robot system easily.展开更多
文摘Clustering is one of the recently challenging tasks since there is an ever.growing amount of data in scientific research and commercial applications. High quality and fast document clustering algorithms are in great demand to deal with large volume of data. The computational requirements for bringing such growing amount data to a central site for clustering are complex. The proposed algorithm uses optimal centroids for K.Means clustering based on Particle Swarm Optimization(PSO).PSO is used to take advantage of its global search ability to provide optimal centroids which aids in generating more compact clusters with improved accuracy. This proposed methodology utilizes Hadoop and Map Reduce framework which provides distributed storage and analysis to support data intensive distributed applications. Experiments were performed on Reuter's and RCV1 document dataset which shows an improvement in accuracy with reduced execution time.
基金The MSIP(Ministry of Science,ICT&Future Planning),Korea,under the ITRC(Information Technology Research Center)Support program(NIPA-2013-H0301-13-2006)supervised by the NIPA(National IT Industry Promotion Agency)
文摘In the distributed environment,robots should be able to provide users with adaptive services automatically according to the situational information changing dynamically which is obtained from both users and their environments.The workflow depends on situational information obtained from physical environments and provides context-aware services automatically based on the information retrieved.And the workflow in the business processes and the distributed computing environments have supported the automation of services by connecting tasks.The workflow needs to specify ubiquitous situational information as state-transition constraints.However,the delivery and use of sensor data in the workflow is a difficult problem for the robot system.In order to bridge the gap between applications and low-level constructs and to acquire raw situational information for the execution of the context-aware workflow in the robot systems,this paper presents an approach which can achieve the sensor data transmission between a sensing server and a robot system easily.
