Research of semantic retrieval system based on domain-ontology and Lucene

2010 ◽  
Vol 30 (6) ◽  
pp. 1655-1657 ◽  
Author(s):  
Huan WANG ◽  
Rui-zhi SUN
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.


2016 ◽  
Vol 25 (3) ◽  
pp. 460-466 ◽  
Author(s):  
Jiajia Hou ◽  
Hui Han ◽  
Chengjing Qiu ◽  
Dongmei Li

2012 ◽  
Vol 19 (2) ◽  
pp. 16-27 ◽  
Author(s):  
Ruben Tous ◽  
Jaime Delgado ◽  
Thomas Zinkl ◽  
Pere Toran ◽  
Gabriela Alcalde ◽  
...  

2013 ◽  
Vol 433-435 ◽  
pp. 1662-1665
Author(s):  
Huan Hai Yang ◽  
Ming Yu Sun

Considering weakness of the traditional retrieval method based on keyword matching, the paper introduced semantic into information retrieval, and proposed a semantic retrieval model based on ontology. The paper offered a construction method of domain ontology and implemented semantic reasoning using Jena and improved a semantic similarity calculation method.


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 488-489 ◽  
pp. 1288-1292
Author(s):  
Min Ren ◽  
Feng Yang

Emergency plan is a project document to guide and deal with public emergency events, and also is the core of emergency management. Nowadays, most emergency plans in China exist in non-semantic form and are difficult to play roles effectively. Ontology is an important method to describe semantic model. Therefore, in this paper, emergency plan ontology model is constructed by ontology technology of semantic Web and Web Ontology Language OWL, which formally describes the conceptions of emergency plan and the relations between them. Finally, the model is used in ontology-based semantic retrieval system, and improves the retrieval recall and precision.


Sign in / Sign up

Export Citation Format

Share Document