WS-Advisor:服务组合框架的任务内存

Rosanna Bova, Hye-young Paik, S. Hassas, S. Benbernou, B. Benatallah
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引用次数: 7

摘要

随着Web服务的激增,支持用户为任务选择最合适的服务组合变得越来越重要。我们提出了一个新的服务发现和选择框架,该框架利用任务记忆的概念和任务记忆的社会网络。任务内存捕获服务组合历史及其元数据,如相关上下文和用户评级。形成任务记忆网络,以实现用户之间有效的任务记忆共享平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WS-Advisor: A Task Memory for Service Composition Frameworks
With the proliferation of Web services, it is becoming increasingly important to support the users in selecting the most appropriate compositions of services for a task. We propose a new service discovery and selection framework that utilises the concept of task memories and a social network of task memories. A task memory captures the service composition history and their meta-data such as associated context and user rating. A network of task memories is formed to realise an effective task memory sharing platform among the users.
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