Research on Semantic Retrieval System for High-Speed Railway Knowledge Based on Ontology

Author(s):  
Ziyu Liu ◽  
Lei Huang ◽  
Dongyun Xu
2011 ◽  
Vol 204-210 ◽  
pp. 2171-2175
Author(s):  
Zi Yu Liu ◽  
Dong Li Zhang ◽  
Xue Hui Li

Domain ontology can effectively organize the knowledge of that domain and make it easier to share and reuse. We can build domain ontology on thesaurus and thematic words and index document knowledge using domain ontology. Under which this paper designs a semantic retrieval system for the document knowledge based on domain ontology, and the system consists of four main components: ontology query, semantic precomputation for document and the concept similarity, semantic extended search and reasoning search. Finally, this paper makes an experiment on high-speed railway domain. The experimental results show that the developed semantic retrieval system can reach the satisfied recall and precision.


2021 ◽  
Vol 11 (1) ◽  
pp. 92-97
Author(s):  
Porawat Visutsak ◽  

In Southeast Asia, durian is affectionately called the king of fruit. Durian is the most popular crop planted in eastern and southern of Thailand. The total crop is around 600,000 tons per year; among this, 500,000 tons of the total production were exported worldwide. In Thailand, the knowledge of durian production is based on experience from generation to generation, especially the knowledge of durian pests and diseases control. This paper presents the ontology knowledge based for durian pests and diseases retrieval system. The major contributions of the system consist of 1) the stored knowledge of durian pests and diseases and 2) the diagnosis of durian diseases and the suggestions for the treatments. The ontology knowledge consists of 8 main classes: 1) diseases, 2) pests, 3) cultivars, 4) symptoms of bunch, 5) leaf area symptoms, 6) symptoms of the branches and trunk, 7) symptoms of fruit, and 8) symptoms of root and growth. The experimental results yielded 100% of precision, 88.33% of recall, and 93.8% of overall performance.


2012 ◽  
Vol 132 (10) ◽  
pp. 673-676
Author(s):  
Takaharu TAKESHITA ◽  
Wataru KITAGAWA ◽  
Inami ASAI ◽  
Hidehiko NAKAZAWA ◽  
Yusuke FURUHASHI

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