Fuzzy-based approach for context-aware service retrieval

M. Madkour, A. Maach, E. Driss, A. Hasbi
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引用次数: 2

Abstract

The idea presented in paper is inspired from the wide prospect given by the integration of fuzzy sets and linguistic quantifiers in the modeling of context and quantification of similarities measurement. In pervasive services retrieval, dealing with context in a flexible and efficient way is extremely important. In this paper we propose a practical classification of context into functional and non functional context. We use the first type in the service discovery with an ontology based model supporting fuzzy context predicates and fuzzy reasoning, while the second type is used for the best-fitting service selection based on the linguistic quantifier “almost all”. Finally, the listed scenario example illustrates the realization and the effectiveness of our approach.
基于模糊的上下文感知服务检索方法
模糊集与语言量词的结合在语境建模和相似性度量量化方面具有广阔的应用前景,这一思路受到了本文的启发。在普适服务检索中,以灵活有效的方式处理上下文非常重要。本文提出了一种实用的语境分类方法:功能语境和非功能语境。我们将第一种类型用于服务发现,并使用基于本体的模型支持模糊上下文谓词和模糊推理,而第二种类型用于基于语言量词“几乎所有”的最佳拟合服务选择。最后,所列出的场景示例说明了我们的方法的实现和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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