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首页> 外文会议>International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies >ONTO SQAM - A Model for Analyzing Seafood Quality Based on Ontology
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ONTO SQAM - A Model for Analyzing Seafood Quality Based on Ontology

机译：ONTO SQAM-基于本体的海鲜质量分析模型

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摘要

One of the most precious exporting sectors in the Indian economy is the seafood industry. Sustained measures to ensure the quality of export materials are very critical to further increase the growth in seafood export. To ensure the overall quality of seafood, a knowledge-based system entitled ‘Ontology Based Quality Analyzer and Miner (ONTO SQAM) is developed. Ontologies are used to represent the seafood domain. Different algorithms are suggested for analysis, mining, and prediction to ensure the seafood quality. The key features of the model are the development of algorithms to generate frequent patterns of quality seafood and to predict the success rates of seafood based on the catching center. Indian Seafood industry is taken as the case study in this research. This paper presents only the architecture of the system. The implementation of the model will be discussed in an extended version of this paper.
机译：海鲜产业是印度经济中最宝贵的出口行业之一。确保出口材料质量的持续措施对于进一步增加海产品出口的增长至关重要。为确保海鲜的整体质量，开发了名为“基于本体的质量分析器和矿机（ONTO SQAM）”的基于知识的系统。本体用于表示海鲜领域。建议使用不同的算法进行分析，挖掘和预测，以确保海鲜质量。该模型的主要特征是开发算法以生成频繁的优质海鲜模式并根据捕获中心预测海鲜的成功率。本研究以印度海鲜产业为例。本文仅介绍系统的体系结构。该模型的实现将在本文的扩展版本中进行讨论。

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