Application of Harmony Search Algorithm to Optimize SPARQL Protocol and Resource Description Framework Query Language Queries in Healthcare Data

G. Ramalingam, S. Dhandapani
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Abstract

The rapid developing international of internet, Semantic Web has become a platform for intelligent agents mainly in the healthcare sector. Inside the beyond few years there is a widening in the Semantic web data field in the healthcare industry. With a growth in the quantity of Semantic web data field in health industry, there exist some challenges to be resolved. One such challenge is to provide an efficient querying mechanism that can handle large number of Semantic web data. Consider many query languages; especially SPARQL (SPARQL Protocol and RDF Query Language) is the most popular query language. Each of these query languages has their own design strategy and it was identified in research that it is difficult to handle and query large quantity of RDF data efficiently using these languages. In the proposed process, Harmony search identify met heuristic algorithm to optimize the SPARQL queries in the healthcare data in the applicable manner. The application of Harmony search algorithm is evaluated with large Resource Description Framework (RDF) datasets and SPARQL queries. To assess performance, the algorithm’s implementation is compared to existing nature-inspired algorithms. The performance analysis shows that the proposed application performs well for large RDF datasets.
和谐搜索算法在优化SPARQL协议和资源描述框架查询语言查询中的应用
随着国际互联网的快速发展,语义网已经成为智能代理的平台,主要应用于医疗保健领域。在未来几年内,医疗行业的语义网数据领域将不断扩大。随着健康行业语义网数据量的不断增长,存在着一些亟待解决的问题。其中一个挑战是提供一种能够处理大量语义web数据的高效查询机制。考虑许多查询语言;特别是SPARQL (SPARQL协议和RDF查询语言)是最流行的查询语言。每一种查询语言都有自己的设计策略,在研究中发现,使用这些语言很难有效地处理和查询大量RDF数据。在提出的流程中,Harmony搜索识别满足启发式算法,以适用的方式优化医疗保健数据中的SPARQL查询。利用大型RDF (Resource Description Framework)数据集和SPARQL查询对Harmony搜索算法的应用进行了评估。为了评估性能,将算法的实现与现有的自然启发算法进行比较。性能分析表明,所提出的应用程序在大型RDF数据集上表现良好。
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