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Web services are a key for today’s e-commerce and are gaining an increasing popularity. Because of availability of extensive variety of services to perform a particular task, it is necessary that users be supported in the ultimate selection of suitable services. For this reason, personalization has become an important aspect in service discovery. Information about service usage is an important component to assess a user’s choice and requirements. This information can be gathered from service access logs. This paper presents a logging and web service usage analysis technique in order to provide a means to ensure appropriate personalized services delivery to a client. By using log analysis with web usage mining statistical information is captured. User is thus offered with a set of services that are most interesting to him. Users are clustered into groups according to their past usage of services, and a potential correlation between web services and user groups is determined, using Fuzzy C-Means (FCM) algorithm. These are obtained on the basis of similarity corresponding to the user profiles that contain state information about a client.
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Dynamic Discovery of Personalized Web Services
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ISBN 10: 6205498898
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Dynamic Discovery of Personalized Web Services
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Dynamic Discovery of Personalized Web Services
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LAP LAMBERT Academic Publishing, 2022
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ISBN 13: 9786205498897
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Dynamic Discovery of Personalized Web Services
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ISBN 13: 9786205498897
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Web services are a key for today's e-commerce and are gaining an increasing popularity. Because of availability of extensive variety of services to perform a particular task, it is necessary that users be supported in the ultimate selection of suitable services. For this reason, personalization has become an important aspect in service discovery. Information about service usage is an important component to assess a user's choice and requirements. This information can be gathered from service access logs. This paper presents a logging and web service usage analysis technique in order to provide a means to ensure appropriate personalized services delivery to a client. By using log analysis with web usage mining statistical information is captured. User is thus offered with a set of services that are most interesting to him. Users are clustered into groups according to their past usage of services, and a potential correlation between web services and user groups is determined, using Fuzzy C-Means (FCM) algorithm. These are obtained on the basis of similarity corresponding to the user profiles that contain state information about a client. 76 pp. Englisch. Bestandsnummer des Verkäufers 9786205498897
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Dynamic Discovery of Personalized Web Services
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205498898
ISBN 13: 9786205498897
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jain Vikas KMr. Vikas K Jain and Mr. Shiv Shankar Prasad Shukla are Assistant Professors in the School of Computing Science and Engineering, VIT Bhopal University. Current research area includes Blockchain, Smart Contract, Machine Le. Bestandsnummer des Verkäufers 732217498
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Dynamic Discovery of Personalized Web Services
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LAP LAMBERT Academic Publishing Sep 2022, 2022
ISBN 10: 6205498898
ISBN 13: 9786205498897
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Taschenbuch. Zustand: Neu. Neuware -Web services are a key for today¿s e-commerce and are gaining an increasing popularity. Because of availability of extensive variety of services to perform a particular task, it is necessary that users be supported in the ultimate selection of suitable services. For this reason, personalization has become an important aspect in service discovery. Information about service usage is an important component to assess a user¿s choice and requirements. This information can be gathered from service access logs. This paper presents a logging and web service usage analysis technique in order to provide a means to ensure appropriate personalized services delivery to a client. By using log analysis with web usage mining statistical information is captured. User is thus offered with a set of services that are most interesting to him. Users are clustered into groups according to their past usage of services, and a potential correlation between web services and user groups is determined, using Fuzzy C-Means (FCM) algorithm. These are obtained on the basis of similarity corresponding to the user profiles that contain state information about a client.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch. Bestandsnummer des Verkäufers 9786205498897
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Dynamic Discovery of Personalized Web Services
Verlag:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205498898
ISBN 13: 9786205498897
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Web services are a key for today's e-commerce and are gaining an increasing popularity. Because of availability of extensive variety of services to perform a particular task, it is necessary that users be supported in the ultimate selection of suitable services. For this reason, personalization has become an important aspect in service discovery. Information about service usage is an important component to assess a user's choice and requirements. This information can be gathered from service access logs. This paper presents a logging and web service usage analysis technique in order to provide a means to ensure appropriate personalized services delivery to a client. By using log analysis with web usage mining statistical information is captured. User is thus offered with a set of services that are most interesting to him. Users are clustered into groups according to their past usage of services, and a potential correlation between web services and user groups is determined, using Fuzzy C-Means (FCM) algorithm. These are obtained on the basis of similarity corresponding to the user profiles that contain state information about a client. Bestandsnummer des Verkäufers 9786205498897
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