Abstract
As growing number of services are being available, selecting the most relevant web service fulfilling the needs of the consumer is indeed challenging. Often consumers may be unaware of precise keywords to retrieve the required services satisfactorily and may be looking for services capable of providing certain outputs. We propose an approach for clustering web services in a registry by utilizing Frequent Service Output Parameter Patterns. The approach looks promising since it provides a natural way of reducing the candidate services when we are looking for a web service with desired output pattern. The experimental results demonstrate the performance of our clustering approach in our Extended Service Registry [5] and the variety of user queries supported.
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H.N., L., Mohanty, H. (2014). Clustering Web Services on Frequent Output Parameters for I/O Based Service Search. In: Murty, M.N., He, X., Chillarige, R.R., Weng, P. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2014. Lecture Notes in Computer Science(), vol 8875. Springer, Cham. https://doi.org/10.1007/978-3-319-13365-2_15
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DOI: https://doi.org/10.1007/978-3-319-13365-2_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13364-5
Online ISBN: 978-3-319-13365-2
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