社会传感器云服务选择

Tooba Aamir, A. Bouguettaya, Hai Dong, A. Erradi, Rachid Hadjidj
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引用次数: 9

摘要

提出了一种基于用户查询与服务之间的空间文本关联的社交传感器云服务选择新框架。本研究定义了一个正式的社会传感器云服务模型,该模型从时空、文本和服务质量参数等方面对云上社会传感器数据的功能和非功能方面进行抽象。提出的框架是一个4阶段的过滤算法,基于用户查询和服务质量需求来选择社交传感器云服务。4级滤波基于空间相关性、文本相关性、视觉特征和服务质量参数。分析结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social-Sensor Cloud Service Selection
We propose a new framework for social-sensor cloud services selection based on spatio-textual correlation between user's query and service. The proposed research defines a formal social-sensor cloud service model that abstracts the functional and non-functional aspects of social-sensor data on the cloud in terms of spatio-temporal, textual and quality of service parameters. Proposed framework is a 4-stage filtering algorithm, to select social-sensor cloud services based on user query and quality of service demands. 4-stage filtering is based on spatial correlation, textual correlation, visual features and quality of service parameters. Analytical results are presented to show the performance of the proposed approach.
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