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

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Abstract

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.

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Authors and Affiliations

  1. Department of Information Technology, Hindustan Institute of Technology and Science, Padur, Kelambakam, Chennai, 603 103, Tamil Nadu, India

    P. Kirubanantham

  2. Department of Information Technology, Velammal Institute of Technology, Panchetti, 601 204, Tamil Nadu, India

    S. M. Udhaya Sankar

  3. School of Computing, Department of Computer Science and Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamilnadu, 603 203, India

    C. Amuthadevi, M. Baskar, M. Senthil Raja & P. C. Karthik

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  1. P. Kirubanantham
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  2. S. M. Udhaya Sankar
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  3. C. Amuthadevi
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  4. M. Baskar
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  5. M. Senthil Raja
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  6. P. C. Karthik
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Correspondence to M. Baskar.

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Kirubanantham, P., Sankar, S.M.U., Amuthadevi, C. et al. An intelligent web service group-based recommendation system for long-term composition. J Supercomput 78, 1944–1960 (2022). https://doi.org/10.1007/s11227-021-03930-1

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