Abstract: Grouping similar operations is an effective solution to the various problems, especially those related to research because the services will be classified by joint operations. Searching for a particular operation returns, as a result, all services with this same operation, but also the problems related to the substitution (such as, during a call failure or a malfunction). A list of similar operations is returned to the client. He chooses an operation, based on non-functional criteria. In this work, our goal is to study the functional similarity between operations, and thus constituting groups of similar operations, while benefiting from the K-means algorithm.

Rekkal Sara, Amrane Fatima and Loukil Lakhdar, “A New Approach for Grouping Similar Operations Extracted from WSDLs Files using K-Means Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 8(12), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081212

@article{Sara2017,
title = {A New Approach for Grouping Similar Operations Extracted from WSDLs Files using K-Means Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081212},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081212},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {12},
author = {Rekkal Sara and Amrane Fatima and Loukil Lakhdar}
}