泰国南部开发研究推荐系统的开发

Nawapon Kewsuwun, Kanyarat Kwiecien, Chumchit Sae-Chan
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引用次数: 1

摘要

该研究旨在确定设计和开发泰国南部14个省发展的研究推荐系统的需求。该系统在2008年1月至2017年12月期间使用语义搜索功能,研究系统结构和知识范围。采用文本分析和知识组织的方法,从泰国图书馆综合系统(thailand Library Integrated System, thailand National Research Repository, TNRR)和南方大学的研究数据库中收集了3873篇文献,并对主要主题进行了分类和分类。在本体的开发上,运用知识工程的理念,按照以用户为中心的设计理念,使用Protege本体编辑器3.5 beta版和5.5 beta版对数据进行处理,进行准确的系统开发。研究结果显示,开发后的系统能够支援资讯交换、资讯检索和研究搜寻,并减少研究冗余和不必要的预算。此外,该系统还可以促进更多的创新,确认该领域的专家,展示研究趋势,并展示相关领域的研究成果,策略和问题,从而促进南方的广泛发展。实施后,用户的总体意见和满意度处于较高水平(X= 4.14, sd = 0.14),系统的信息检索效率处于较好的水平(总体= 0.70-0.88),正确率为0.70,召回率为0.78,精密度为0.88,F-measure为0.82。
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The Development of Research Recommendation System for Southern Thailand Development
The research was to identify needs on design and development of a research recommendation system for 14 southern province Thailand development. The system employs semantic search function, research system structure and scope of knowledge during January 2008 to December 2017. 3,873 entries had been gathered from Thai Library Integrated System (ThaiLIS), Thai National Research Repository (TNRR), and Southern universities research database by employing textual analysis and knowledge organization focusing on Classification Approach and categorization which main topics are sorted and categorized. To develop ontology, it applies knowledge engineering concept and using Protege Ontology Editor version 3.5 beta and version 5.5 beta to process the data for the accurate system development according to user-centered design concept. The study findings were the developed system is able to support information exchange, information retrieval, and research search and to decrease research redundancy and unnecessary budgeting. Moreover, the system could possible enhance conducting more innovations, confirming experts in the area, showing research trends, and showing research results on related fields, strategies, and problems which leads to the Southern developments extensively. After the implementation, the users’ overall opinions and satisfaction was at a high level (X= 4.14, S.D = 0.14) and information retrieval efficiency of system was at a good level (overall = 0.70-0.88) with 0.70 accuracy, 0.78 recall, 0.88 precision, and 0.82 F-measure.
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