F
Fernando Lemos
Researcher at Federal University of Ceará
Publications - 20
Citations - 85
Fernando Lemos is an academic researcher from Federal University of Ceará. The author has contributed to research in topics: Service discovery & Quality of service. The author has an hindex of 5, co-authored 20 publications receiving 83 citations.
Papers
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Book ChapterDOI
Selecting and ranking business processes with preferences: an approach based on fuzzy sets
Katia Abbaci,Fernando Lemos,Allel Hadjali,Daniela Grigori,Ludovic Liétard,Daniel Rocacher,Mokrane Bouzeghoub +6 more
TL;DR: In this paper, the authors propose and evaluate a novel approach for service retrieval that takes into account the service process model and relies both on preference satisfiability and structural similarity, where user preferences on QoS attributes are modelled by means of fuzzy sets.
Proceedings ArticleDOI
Towards automatic generation of AXML web services for dynamic data integration
TL;DR: This paper presents a framework for generation of AXML Web services for materializing the dynamic content of Web pages in data intensive Web sites, and focuses on an algorithm that automatically generates the Web service that materializes the view's content.
Proceedings Article
A mapping-driven approach for sql/xml view maintenance
TL;DR: This work studies the problem of how to incrementally maintain materialized XML views of relational data, based on the semantic mappings that model the relationship between the source and view schemas.
Proceedings Article
Towards automatic generation of application ontologies
Eveline R. Sacramento,Vânia Maria Ponte Vidal,José Antônio Fernandes de Macêdo,Bernadette Farias Lóscio,Fernanda Lígia R. Lopes,Fernando Lemos,Marco A. Casanova +6 more
TL;DR: In this paper, the authors propose a strategy to automatically generate applica- tion ontologies, considering a set of local ontologies and a domain ontology, and the result of the matching between each local ontology and the domain ontologies.
Book ChapterDOI
Adding non-functional preferences to service discovery
TL;DR: This paper presents an approach to extend structure-based service discovery by making it sensitive to user preferences over service quality defined at different granularity levels of the service structure.