Mash up Candidate Prediction: A Survey on Mashup Techniques, Tools and Framework

Authors

  • Suganya P Assistant Professor, Department of Information Technology, EGS Pillay Engineering College, Nagapattinam, Tamilnadu, India
  • Lavanya S Assistant Professor, Department of Information Technology, EGS Pillay Engineering College, Nagapattinam, Tamilnadu, India
  • Vijayavani E Assistant Professor, Department of Information Technology, EGS Pillay Engineering College, Nagapattinam, Tamilnadu, India
  • Elakiya E Assistant Professor, Department of Information Technology, EGS Pillay Engineering College, Nagapattinam, Tamilnadu, India

Keywords:

Service Oriented Computing, Service Mashup, Distributed Services

Abstract

The evolution of web 2.0 introduces the complementary features of service composition which focuses on community and usability of web services. The increasing number of applications on the web and a growing need to combine them in order to meet user requirements.. Mashup is the process of assimilating web services for generating new services; it extracts data from various resources like PDFs, databases, legacy systems, and web applications. Before performing Mashup, the possible candidates for aggregation should be generated. In dynamically changing internet scenario, predicting service Mashup candidates are tedious one. This paper uses Syntactic technique to predict candidates and used for determine the equivalences among the services with reasonable precision, and it also analyzes the naming tendency of web service developers. The result makes the service search process to identify candidate services faster. This paper deals with the design of client side Mashup architecture with viable candidates for aggregating services. The system has a pallet of services that are clustered by their input and output. It would involve service connection, composition and data visualization. This framework allows users to play with services.

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Published

2024-02-26

How to Cite

Suganya, P., Lavanya, S., Vijayavani, E., & Elakiya, E. (2024). Mash up Candidate Prediction: A Survey on Mashup Techniques, Tools and Framework. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(06), 973–979. Retrieved from https://ijact.in/index.php/j/article/view/170

Issue

Section

Review Article

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