Automatic service categorisation through machine learning in emergent middleware

Amel Bennaceur, Valérie Issarny, Richard Johansson, Alessandro Moschitti, Romina Spalazzese, Daniel Sykes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The modern environment of mobile, pervasive, evolving services presents a great challenge to traditional solutions for enabling interoperability. Automated solutions appear to be the only way to achieve interoperability with the needed level of flexibility and scalability. While necessary, the techniques used to determine compatibility, as a precursor to interaction, come at a substantial computational cost, especially when checks are performed between systems in unrelated domains. To overcome this, we apply machine learning to extract high-level functionality information through text categorisation of a system's interface description. This categorisation allows us to restrict the scope of compatibility checks, giving an overall performance gain when conducting matchmaking between systems. We have evaluated our approach on a corpus of web service descriptions, where even with moderate categorisation accuracy, a substantial performance benefit can be found. This in turn improves the applicability of our overall approach for achieving interoperability in the Connect project.

Original languageEnglish
Title of host publicationFormal Methods for Components and Objects - 10th International Symposium, FMCO 2011, Revised Selected Papers
Pages133-149
Number of pages17
DOIs
Publication statusPublished - 5 Sep 2013
Event10th International Symposium on Formal Methods for Components and Objects, FMCO 2011 - Turin, Italy
Duration: 3 Oct 20115 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7542 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Symposium on Formal Methods for Components and Objects, FMCO 2011
CountryItaly
CityTurin
Period3/10/115/10/11

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Bennaceur, A., Issarny, V., Johansson, R., Moschitti, A., Spalazzese, R., & Sykes, D. (2013). Automatic service categorisation through machine learning in emergent middleware. In Formal Methods for Components and Objects - 10th International Symposium, FMCO 2011, Revised Selected Papers (pp. 133-149). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7542 LNCS). https://doi.org/10.1007/978-3-642-35887-6-7