Dynamic Discovery of Personalized Web Services

Vikas K Jain

ISBN 10: 6205498898 / ISBN 13: 9786205498897

Editore: LAP LAMBERT Academic Publishing Sep 2022, 2022

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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.

Codice articolo 9786205498897

Dati bibliografici

• Titolo: Dynamic Discovery of Personalized Web Services
• Editore: LAP LAMBERT Academic Publishing Sep 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 6205498898
• ISBN 13: 9786205498897
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 5 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 5 millimetri di profondità
• Peso: 131 grammi

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Riassunto

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.