Data-Centered Service Composition for Information Analysis

Abstract

In e-Science, many scientific workflow management systems have been developed to integrate distributed computation resources, data sets, and mining algorithms. Users usually modify and rerun a workflow while repeating procedures: preprocess of data, selection of features, modification of data, selection of mining algorithms, generation of models, and evaluation of the models. These procedures are continued until the domain knowledge is acquired. However, as the size of the data increases, the execution time of the workflow becomes longer and longer, which drives up the cost of rerunning the modified workflow. As a result, it becomes hard to quickly obtain the analysis result. In this research, we avoided the rerun of the workflow by storing service invocation results on a platform and realized data-centered service composition by adding and deleting rules to be fired. To validate the effectiveness of our proposed platform, we created two rulebased services to analyze real-time data: stream message data and sensing data.

Optimizing Web Service Composition for Data-intensive Applications

“…As the size of data increases, the execution time becomes much longer. Murakami et al, consider storing service invocation results to avoid rerunning the workflow [13]. Although a lot of researches have been done, none mentioned the optimization based on the parallelism of Web services.…”

Classification methods comparison for customer churn prediction in the telecommunication industry

“…Hence, this research compares five well-known classification methods to find the best accuracy, precision, and recall in analyzing the customer churn that is not yet presented in previous research. Moreover, we partly base the analysis work on our previous experience (Bramantoro et al, 2015;Murakami et al, 2012).…”

Cloud-based learning service platform for multilingual smart class

“…The main technique to implement this project is XaaS., especially with everything in the cloud nowadays, and everything can be easier to be wrapped as a service. Additional functionality and non-functionality are possible to be added to the existing platform by using Web service technology (Murakami et al, 2012b). Hence, all services from the existing application and data, and all new services are in one single platform, i.e., Learning Service Platform, in order to choreograph and orchestrate into a better learning process in the university.…”