Implementation of integrated mashup service a concepts

Abstract

Academia and industries are showing great deal of interest in integration of various web services. Result of numerous corresponding web services merged into one, which leads to discovery of new types of information. With the advent of Web 2.0, there has been a substantial increase in development and usage of E-commerce websites. But this has also lead to new arenas of requirements that open up such has an efficient data mining technology for searching, robust & reliable infrastructure. Amalgamation of web 2.0 and integrated web mashup services give advantages to user. As a result, user can interact easily with different types of services as per application of interest. Integrated mashup service system used user behavior analysis for clustering of data. Data of various web services is clustered by using Euclidean distance algorithm. Finally structured output is shown to the user based multiple predictions of particular user. This paper adopts Knowledge Discovery in Services (KDS) process, which leads to discover new type of data.