The Experts below are selected from a list of 19809 Experts worldwide ranked by ideXlab platform
Mokrane Bouzeghoub - One of the best experts on this subject based on the ideXlab platform.
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A Fuzzy Set Approach to Handle Preferences in Service Retrieval
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Mokrane Bouzeghoub, Daniel RocacherAbstract:Abstract. Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
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Selecting and Ranking Business Process with Preferences: An Approach Based on Fuzzy Set
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behaviour. One way to improve the selectivity rate and to provide the best suited Services is to cope with user preferences defined on quality attributes. In this paper, we 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. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A fexible evaluation strategy based on fuzzy linguistic quantifiers (such as almost all) is introduced. Then, two families of ranking methods are discussed. Finally, an extensive set of experiments based on real data sets is conducted, on the one hand, to demonstrate the efficiency and the scalability of our approach, and on the other hand, to analyze the effectiveness and the accuracy of the proposed ranking methods compared to expert evaluation.
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Selecting and Ranking Business Processes with Preferences: An Approach Based on Fuzzy Sets
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate and to provide the best suited Services is to cope with user preferences defined on quality attributes. In this paper, we 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. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers (such as almost all) is introduced. Then, two families of ranking methods are discussed. Finally, an extensive set of experiments based on real data sets is conducted, on one hand, to demonstrate the efficiency and the scalability of our approach, and on the other hand, to analyze the effectiveness and the accuracy of the proposed ranking methods compared to expert evaluation.
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An Approach Based on Fuzzy Sets to Handle Preferences in Service Retrieval
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches have high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
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An Approach Based on Fuzzy Sets to Selecting and Ranking Business Processes
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches have high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
Daniela Grigori - One of the best experts on this subject based on the ideXlab platform.
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A Fuzzy Set Approach to Handle Preferences in Service Retrieval
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Mokrane Bouzeghoub, Daniel RocacherAbstract:Abstract. Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
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Selecting and Ranking Business Process with Preferences: An Approach Based on Fuzzy Set
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behaviour. One way to improve the selectivity rate and to provide the best suited Services is to cope with user preferences defined on quality attributes. In this paper, we 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. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A fexible evaluation strategy based on fuzzy linguistic quantifiers (such as almost all) is introduced. Then, two families of ranking methods are discussed. Finally, an extensive set of experiments based on real data sets is conducted, on the one hand, to demonstrate the efficiency and the scalability of our approach, and on the other hand, to analyze the effectiveness and the accuracy of the proposed ranking methods compared to expert evaluation.
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Selecting and Ranking Business Processes with Preferences: An Approach Based on Fuzzy Sets
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate and to provide the best suited Services is to cope with user preferences defined on quality attributes. In this paper, we 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. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers (such as almost all) is introduced. Then, two families of ranking methods are discussed. Finally, an extensive set of experiments based on real data sets is conducted, on one hand, to demonstrate the efficiency and the scalability of our approach, and on the other hand, to analyze the effectiveness and the accuracy of the proposed ranking methods compared to expert evaluation.
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An Approach Based on Fuzzy Sets to Handle Preferences in Service Retrieval
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches have high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
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An Approach Based on Fuzzy Sets to Selecting and Ranking Business Processes
2011Co-Authors: Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, Daniel Rocacher, Mokrane BouzeghoubAbstract:Current approaches for Service discovery are based on semantic knowledge, such as ontologies and Service behavior (described as a process model). However, these approaches have high selectivity rate, resulting in a large number of Services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for Service Retrieval that takes into account the Service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
Elizabeth Chang - One of the best experts on this subject based on the ideXlab platform.
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A Human-Centered Semantic Service Platform for the Digital Ecosystems Environment
World Wide Web, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystems (DEST) have emerged with the purpose of enhancing communications among small and medium enterprises (SMEs) within the worldwide Business Ecosystem. However, because of the diversity and heterogeneity of the Services in the DEST environment, existing commercial products or research outputs cannot be directly applied to this field so as to fulfill the requirements of SMEs. Human-centered computing has been applied to many areas, such as social classification, community-based ontology evolution, and more importantly, human-centered systems. In this paper, we propose a framework for a human-centered semantic Service platform, in order to address the issue in the DEST environment. This framework incorporates the features of human-centered metadata publishing, maintenance and clustering, community-based ontology revolution and human-centered Service Retrieval, evaluation and ranking. To thoroughly validate the framework, we implement a prototype in the transport Service domain, and conduct a series of evaluation experiments on the basis of this prototype.
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Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.
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CISIS - Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.
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A QoS-based Service Retrieval methodology for digital ecosystems
International Journal of Web and Grid Services, 2009Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:The emergence of the World Wide Web and its influence on the fields of industry, commerce, healthcare and so on, has led to an innovative, dynamic, open, collaborative and interactive environment – the digital ecosystem. Whereas Service plays an important role in digital ecosystems, there is no technology available to retrieve heterogeneous and geographically dispersed Services. Additionally, no methodology has been proposed in the literature that can distinguish or rank the Services based on the Quality of Services (QoS). In order to address these issues, we propose a semantic Service Retrieval engine which incorporates a novel semantic QoS evaluation methodology. The salient feature of this methodology that sets it apart from any other QoS evaluation methodologies is that the evaluation of the Service and the subsequent quantification of QoS is a combination of subjective and objective QoS measures. Another salient feature of our proposed methodology is that it enables the domain-specific ranking of Services. Finally, an online prototype is implemented to evaluate our methodology, the results of which are discussed in this paper.
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MoMM - Quality of Service (QoS) based Service Retrieval engine
Proceedings of the 6th International Conference on Advances in Mobile Computing and Multimedia - MoMM '08, 2008Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:It is observed that there are few Service evaluation and ranking methodologies currently available in the SOE. In this paper, we propose an innovative Service evaluation and ranking strategy, based on the measurement of trustworthiness and reputation of Services (or Service providers'). CCCI Metrics originally proposed and developed by Chang et al [1] is used to measure the trustworthiness and reputation of e-Services. Here we extend the application of CCCI Metrics to the field of Service Retrieval. A java-based search engine prototype is designed, with the purpose of implementing the trustworthiness and reputation-based Service search, evaluation and ranking. Conclusions and future works are drawn in the final section.
Hai Dong - One of the best experts on this subject based on the ideXlab platform.
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ICONIP (3) - A fuzzy VSM-based approach for semantic Service Retrieval
Neural Information Processing, 2014Co-Authors: Supannada Chotipant, Hai Dong, Farookh Khadeer Hussain, Omar Khadeer HussainAbstract:A vast number of business Services have been published on the Web in an attempt to achieve cost reductions and satisfy user demand. Service Retrieval consequently plays an important role, but unfortunately existing research focuses on crisp Service Retrieval techniques which are unsuitable for vague real world information. In this paper, we propose a new fuzzy Service Retrieval approach which consists of two modules: Service annotation and Service Retrieval. Related Service concepts for a given query are semantically retrieved, following which Services that are annotated to those concepts are retrieved. The degree of Retrieval of the Retrieval module and the similarity between a Service, a concept, and a query are fuzzy. Our experiment shows that the proposed approach performs better than a non-fuzzy approach on Recall measure.
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A Human-Centered Semantic Service Platform for the Digital Ecosystems Environment
World Wide Web, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystems (DEST) have emerged with the purpose of enhancing communications among small and medium enterprises (SMEs) within the worldwide Business Ecosystem. However, because of the diversity and heterogeneity of the Services in the DEST environment, existing commercial products or research outputs cannot be directly applied to this field so as to fulfill the requirements of SMEs. Human-centered computing has been applied to many areas, such as social classification, community-based ontology evolution, and more importantly, human-centered systems. In this paper, we propose a framework for a human-centered semantic Service platform, in order to address the issue in the DEST environment. This framework incorporates the features of human-centered metadata publishing, maintenance and clustering, community-based ontology revolution and human-centered Service Retrieval, evaluation and ranking. To thoroughly validate the framework, we implement a prototype in the transport Service domain, and conduct a series of evaluation experiments on the basis of this prototype.
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Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.
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CISIS - Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.
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A QoS-based Service Retrieval methodology for digital ecosystems
International Journal of Web and Grid Services, 2009Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:The emergence of the World Wide Web and its influence on the fields of industry, commerce, healthcare and so on, has led to an innovative, dynamic, open, collaborative and interactive environment – the digital ecosystem. Whereas Service plays an important role in digital ecosystems, there is no technology available to retrieve heterogeneous and geographically dispersed Services. Additionally, no methodology has been proposed in the literature that can distinguish or rank the Services based on the Quality of Services (QoS). In order to address these issues, we propose a semantic Service Retrieval engine which incorporates a novel semantic QoS evaluation methodology. The salient feature of this methodology that sets it apart from any other QoS evaluation methodologies is that the evaluation of the Service and the subsequent quantification of QoS is a combination of subjective and objective QoS measures. Another salient feature of our proposed methodology is that it enables the domain-specific ranking of Services. Finally, an online prototype is implemented to evaluate our methodology, the results of which are discussed in this paper.
Farookh Khadeer Hussain - One of the best experts on this subject based on the ideXlab platform.
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SERNOTATE: An automated approach for business Service description annotation for efficient Service Retrieval and composition
Concurrency and Computation: Practice and Experience, 2017Co-Authors: Supannada Chotipant, Farookh Khadeer Hussain, Omar Khadeer HussainAbstract:Summary Business Service advertisements are today published online to convey essential information about Services to customers. However, current Web search engines are unable to search and combine online Service advertisements. Semantic Service annotation is important for its ability to enable machines to understand the meaning of Services and support in effective Service Retrieval and Service composition. Existing research in the area of semantic Service annotation has focused on the annotation of Web Services in a semi-automated approach. It cannot be applied to business Service information as it is not in the form of Web Services Description Language but in free text format. Moreover, semi-automated approaches are inappropriate for annotating a large amount of online Service information which changes dynamically and they are therefore not suitable for the timely dissemination of Service information to customers. To solve these issues, we propose SERNOTATE, which is an automated approach for business Service description annotation for efficient Service Retrieval and composition. We propose new semantic-based linking approaches, namely, Extended Case-based Reasoning, vector-based, and classification-based, that automatically annotate business Services to relevant Service concepts. Each approach assists in the single-label and multi-label annotation of Service terms to concept terms to provide a better representation of Services. The experimental results test and validate the applicability of the proposed approaches to the automatic annotation of business Service descriptions to Service concepts on a real-world dataset.
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FUZZ-IEEE - An automated and fuzzy approach for semantically annotating Services
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2015Co-Authors: Supannada Chotipant, Farookh Khadeer Hussain, Omar Khadeer HussainAbstract:In the recent past, semantic technologies have played an significant role in Service Retrieval and Service querying. Annotating Services semantically enables machines to understand the purpose of Services and can further assist in intelligent and precise Service Retrieval, selection and composition. A key issue in semantically annotating Services is the manual nature of Service annotation. Manual Service annotation requires a large amount of time and updating happens infrequently, hence annotations may get out-of-date due to Service description changes. Although some researchers have studied semantic Service annotation, they have only focused on web Services not business Service information. Moreover, their approaches are semi-automated, and still require Service providers to select appropriate Service annotations. In this paper, we propose a completely automated semantic annotation approach for e-Services. The aim of this paper is to semantically annotate a Service to relevant Service concepts in domain-specific ontologies. Services and Service concepts are represented by an extended VSM model, based on fuzzy rules. Then, we link a Service to a concept, based on the similarity value of the representing vectors. We found during the experimentation process that the performances of the proposed approach and the VSM-based approach were quite similar and, as a result, developed a system to retrieve Services that are annotated to relevant concepts. Experiments using a high Service Retrieval threshold demonstrated a Retrieval approach based on extended VSM annotation performed much better than an approach based on VSM annotation.
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ICONIP (3) - A fuzzy VSM-based approach for semantic Service Retrieval
Neural Information Processing, 2014Co-Authors: Supannada Chotipant, Hai Dong, Farookh Khadeer Hussain, Omar Khadeer HussainAbstract:A vast number of business Services have been published on the Web in an attempt to achieve cost reductions and satisfy user demand. Service Retrieval consequently plays an important role, but unfortunately existing research focuses on crisp Service Retrieval techniques which are unsuitable for vague real world information. In this paper, we propose a new fuzzy Service Retrieval approach which consists of two modules: Service annotation and Service Retrieval. Related Service concepts for a given query are semantically retrieved, following which Services that are annotated to those concepts are retrieved. The degree of Retrieval of the Retrieval module and the similarity between a Service, a concept, and a query are fuzzy. Our experiment shows that the proposed approach performs better than a non-fuzzy approach on Recall measure.
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Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.
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CISIS - Semantic Service Retrieval and QoS Measurement in the Digital Ecosystem Environment
2010 International Conference on Complex Intelligent and Software Intensive Systems, 2010Co-Authors: Hai Dong, Farookh Khadeer Hussain, Elizabeth ChangAbstract:Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of Service Retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a Service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of Service information and a set of unified QoS measurement for Service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.