@inproceedings{6ddbab9b69004edf894461445343c454,
title = "PMRF: Parameterized Matching-Ranking Framework",
abstract = "The PMRF (Parameterized Matching-Ranking Framework) is a highly configurable framework supporting a parameterized matching and ranking of Web services. This paper first introduces the matching and ranking algorithms supported by the PMRF. Next, it presents the architecture of the developed system and discusses some implementation issues. Then, it provides the results of performance evaluation of the PMRF. It also compares PMRF to two exiting frameworks, namely iSeM-logic-based and SPARQLent. The different matching and ranking algorithms have been evaluated using the OWLS-TC4 datasets. The evaluation has been conducted employing the SME2 (Semantic Matchmaker Evaluation Environment) tool. The results show that the algorithms behave globally well in comparison to iSeM-logic-based and SPARQLent.",
keywords = " Web service, Service composition, Semantic similarity, Matchmaking, Service ranking",
author = "Fatma-Ezzahra Gmati and Nadia Yacoubi-Ayadi and Afef Bahri and Salem Chakhar and Alessio Ishizaka",
year = "2016",
month = jun,
day = "3",
doi = "10.1007/978-3-319-33903-0_13",
language = "English",
isbn = "978-3-319-33903-0",
series = "Studies in Computational Intelligence",
publisher = "Springer",
pages = "181--198",
editor = "Roger Lee",
booktitle = "Software engineering research, management and applications",
note = "14th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications, SERA 2016 ; Conference date: 08-06-2016 Through 10-06-2016",
url = "http://orion.towson.edu/~sera/2016/index.html",
}