Novel recommendation system based on long-term composition for adaptive web services

In the era of digital web services, composition of features on the fly is inevitable. The Long-term Composed Service (LCS) entertains the composition of features to any extent, since it has an open-ended lifetime. In the proposed research work, we have intended to provide service support to run the business toward a long time commitment. Structure-based recommended system for LCSs (RS-LCSs) is proposed, where user queries and recent updation/requirements are considered for exhibiting the response through the system. In the proposed system, business has been regulated according to the time constraints. We have tested our proposed system on the standard benchmark dataset and quantitative metrics show our proposed method has performed well against the compared methods. The forecasting of business has been done through our model to address the recent queries and new requirements issues to provide an adaptive web service for the business development.     

An intelligent web service group-based recommendation system for long-term composition

A modern model long-term composed service (LCS) with a group recommendation system has an indefinite lifespan. An LCS is used as a long-term business goal, and for a business committed to its customers, support will be provided to customers enabling them to book, e.g. an automotive service through online web services by providing information that the LCS then uses to offer more support. However, identifying the exact service to meet the user requirement is essential. Service composition has been identified as the key task in achieving various QoS performances. There exist various approaches that involve service composition according to the throughput and popularity. However, they fail to achieve the expected performance. Towards improving the performance of the LCS, a novel LCS that is based on the user queries of a group of persons is developed to give the best business services based on previous travel details and services. The method carries out service selection and composition according to the ratings provided by users towards any service. Additionally, the method considers the user-to-service rating and service-to-service rating, which are measured according to the coupling quality. Therefore, the proposed novel LCS provides better services based on the user ratings for particular business queries. The method ranks the services according to the rating values to perform service composition, with consideration of the detection of similar user groups and utilization of the rating values in service selection. We aim to propose a novel LCS work based on group ratings and a group of services. This work is intended to reduce the time complexity of changes in the LCS network using the group recommendation system.