HOU Jiajia, LI Dongmei, QIU Chengjing, et al., “A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests,” Chinese Journal of Electronics, vol. 25, no. 3, pp. 460-466, 2016, doi: 10.1049/cje.2016.05.011
Citation: HOU Jiajia, LI Dongmei, QIU Chengjing, et al., “A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests,” Chinese Journal of Electronics, vol. 25, no. 3, pp. 460-466, 2016, doi: 10.1049/cje.2016.05.011

A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests

doi: 10.1049/cje.2016.05.011
Funds:  This work is supported by the Fundamental Research Funds for the Central Universities (No.TD2014-02, No.YX2014-19).
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  • Corresponding author: LI Dongmei received the Ph.D. degree from Beijing Jiaotong University in 2014. She is an associate professor in School of Information and technology at Beijing Forestry University. Her research interests include artificial intelligent, knowledge engineering and semantic Web. (Email: lidongmei@bjfu.edu.cn)
  • Received Date: 2014-12-17
  • Rev Recd Date: 2015-01-28
  • Publish Date: 2016-05-10
  • Ontology-based semantic retrieval can improve the efficiency of information retrieval. This paper proposes a semantic retrieval model based on domain ontology of orchard disease and pests. According to Forestry Thesaurus, we semi-automatically construct a domain ontology and repair ontology inconsistency to ensure the accuracy and uniqueness of the domain knowledge. A concept similarity algorithm is proposed and applied to calculate sentence similarity. We present a synthetic sentence similarity algorithm, which is a combination of the traditional sentence similarity algorithm and the weighted sentence similarity algorithm. Compared with other related methods through experiments, our retrieval model has higher accuracy in semantic retrieval.
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