Recommendations for web service composition by mining usage logs

TL;DR

This paper explores methods to mine web service usage logs to identify service associations, link invocations, and evaluate causal relationships, aiming to improve web service composition based on actual usage patterns.

Contribution

It introduces novel techniques for mining usage logs to enhance web service composition by leveraging real-world invocation patterns and causal relationships.

Findings

Identified usage associations among web services.

Linked service invocations based on usage patterns.

Evaluated causal relationships between service associations.

Abstract

Web service composition has been one of the most researched topics of the past decade. Novel methods of web service composition are being proposed in the literature include Semantics-based composition, WSDLbased composition. Although these methods provide promising results for composition, search and discovery of web service based on QoS parameter of network and semantics or ontology associated with WSDL, they do not address composition based on usage of web service. Web Service usage logs capture time series data of web service invocation by business objects, which innately captures patterns or workflows associated with business operations. Web service composition based on such patterns and workflows can greatly streamline the business operations. In this research work, we try to explore and implement methods of mining web service usage logs. Main objectives include Identifying usage association of services. Linking one service invocation with other, Evaluation of the causal relationship between associations of services