|Date:||March 07, 2013|
School of Computing & Information Sciences
Florida International University
Cloud services marketplace (CSM) is an exploratory project aiming to provide “an AppStore for Services”. It is an intelligent online marketplace that facilitates services acquisition for enterprise customers. Traditional service acquisition is time-consuming and unable to provide customers with a systematic comparison of candidate services. In the era of OneClick Checkout and pay-as-you-go service plans, customers expect services to be purchased online in an efficient and convenient manner. However, due to the unique and complex characteristics of services, existing keyword search based marketplaces are less suitable for purchasing services. Therefore, a new generation of marketplace interfaces is needed. In CSM, exploring and configuring services is an iterative experience. The customers provide their requirements in natural language and interact with the system through a series of questions and answers. Based on customer’s input, the system can gradually “understand” what services the customer is looking for, narrowing down the potential candidates and profiling the configuration information of the candidate services at the same time. CSM’s back end is built around a Services Knowledge Base (SKB) and leverages semantic web technologies to enable the semantical understanding of the customer’s requirements. To quantitatively assess the value of CSM, we conducted experiments on real life use cases. The evaluation results demonstrate the efficiency and convenience of this new service acquisition approach.
Yexi Jiang is currently a third year Ph.D student in the School of Computing and Information Science, Florida International University. His advisor is Professor Tao Li. Before came to FIU, he received his B.E. and M.S. in Sichuan University of China in 2007 and 2010 respectively. Yexi Jiang's research interests includes System Oriented Data Mining, Large Scale Data Mining, Semantic Web, Cloud Analytics, Database and Information Retrieval.