A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment

A Service Ecosystem is a biological view of the business and software environment, which is comprised of a Service Use Ecosystem and a Service Supply Ecosystem. Service matchmakers play an important role in ensuring the connectivity between the two ecosystems. Current matchmakers attempt to employ o...

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Main Authors: Dong, Hai, Hussain, Farookh Khadeer, Chang, Elizabeth
Format: Journal Article
Published: Academic Press 2010
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/12042
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author Dong, Hai
Hussain, Farookh Khadeer
Chang, Elizabeth
author_facet Dong, Hai
Hussain, Farookh Khadeer
Chang, Elizabeth
author_sort Dong, Hai
building Curtin Institutional Repository
collection Online Access
description A Service Ecosystem is a biological view of the business and software environment, which is comprised of a Service Use Ecosystem and a Service Supply Ecosystem. Service matchmakers play an important role in ensuring the connectivity between the two ecosystems. Current matchmakers attempt to employ ontologies to disambiguate service consumers’ service queries by semantically classifying service entities and providing a series of human computer interactions to service consumers. However, the lack of relevant service domain knowledge and the wrong service queries could prevent the semantic service matchmakers from seeking the service concepts that can be used to correctly represent service requests. To resolve this issue, in this paper, we propose the framework of a service concept recommendation system, which is built upon a semantic similarity model.This system can be employed to seek the concepts used to correctly represent service consumers’ requests, when a semantic service matchmaker finds that the service concepts that are eventually retrieved cannot match the service requests. Whilst many similar semantic similarity models have been developed to date, most of them focus on distance-based measures for the semantic network environment and ignore content-based measures for the ontology environment. For the ontology environment in which concepts are defined with sufficient datatype properties, object properties, and restrictions etc., the content of concepts should be regarded as an important factor in concept similarity measures. Hence, we present a novel semantic similarity model for the service ontology environment. The technical details and evaluation details of the framework are discussed in this paper.
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spelling curtin-20.500.11937-120422019-02-19T04:27:47Z A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth Semantic similarity models Service ontology Service ecosystem Service concept recommender system Semantic service matchmakers A Service Ecosystem is a biological view of the business and software environment, which is comprised of a Service Use Ecosystem and a Service Supply Ecosystem. Service matchmakers play an important role in ensuring the connectivity between the two ecosystems. Current matchmakers attempt to employ ontologies to disambiguate service consumers’ service queries by semantically classifying service entities and providing a series of human computer interactions to service consumers. However, the lack of relevant service domain knowledge and the wrong service queries could prevent the semantic service matchmakers from seeking the service concepts that can be used to correctly represent service requests. To resolve this issue, in this paper, we propose the framework of a service concept recommendation system, which is built upon a semantic similarity model.This system can be employed to seek the concepts used to correctly represent service consumers’ requests, when a semantic service matchmaker finds that the service concepts that are eventually retrieved cannot match the service requests. Whilst many similar semantic similarity models have been developed to date, most of them focus on distance-based measures for the semantic network environment and ignore content-based measures for the ontology environment. For the ontology environment in which concepts are defined with sufficient datatype properties, object properties, and restrictions etc., the content of concepts should be regarded as an important factor in concept similarity measures. Hence, we present a novel semantic similarity model for the service ontology environment. The technical details and evaluation details of the framework are discussed in this paper. 2010 Journal Article http://hdl.handle.net/20.500.11937/12042 10.1016/j.jnca.2010.11.010 Academic Press fulltext
spellingShingle Semantic similarity models
Service ontology
Service ecosystem
Service concept recommender system
Semantic service matchmakers
Dong, Hai
Hussain, Farookh Khadeer
Chang, Elizabeth
A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title_full A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title_fullStr A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title_full_unstemmed A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title_short A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
title_sort service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment
topic Semantic similarity models
Service ontology
Service ecosystem
Service concept recommender system
Semantic service matchmakers
url http://hdl.handle.net/20.500.11937/12042