HOU Jiajia, LI Dongmei, QIU Chengjing, HAN Hui. A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests[J]. Chinese Journal of Electronics, 2016, 25(3): 460-466. doi: 10.1049/cje.2016.05.011
Citation: HOU Jiajia, LI Dongmei, QIU Chengjing, HAN Hui. A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests[J]. Chinese Journal of Electronics, 2016, 25(3): 460-466. 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).
More Information
  • 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.
  • loading
  • J. Wu, Z.H. Wu, Y. Li and S.G. Deng, "Web service discovery based on ontology and similarity of words", Chinese Journal of Computers, Vol.28, No.4, pp.595-602, 2005.
    D.X. Cao, Z.J. Li and R. Karthik, "Ontology-based customer preference modeling for concept generation", Advanced Engineering Informatics, Vol.25, No.2, pp.162-176, 2011.
    S. Zammali, K. Arour and A. Bouzeghoub, "Using ontologies to build testbed for peer-to-peer information retrieval systems", Proc. of the 27th IEEE International Conference on Advanced Information Networking and Applications (AINA), Barcelona, Spain, pp.1033-1040, 2013.
    S.T. Cheng, C.L. Chou and G.J. Horng, "The adaptive ontology-based personalized recommender system", Wireless Personal Communications, Vol.72, No.4, pp.1801-1826, 2011.
    D.M. Li, J.J. Hou, et al., "A computation study on semantics based weighted sentence similarity", Journal of Chemical and Pharmaceutical Research, Vol.5, No.8, pp.225-231, 2013.
    C. Willis and R.M. Losee, "A random walk on an ontology: Using thesaurus structure for automatic subject indexing", Journal of the American Society for Information Science and Technology, Vol.64, No.7, pp.1330-1344, 2013.
    J.F. Du, G.L. Qi, J.Z. Pan, et al., "A decomposition-based approach to OWL DL ontology diagnosis", Proc. of the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Florida, USA, pp.659-664, 2011.
    Z.S. Huang and F.V. Harmelen, "Using semantic distances for reasoning with inconsistent ontologies", Proc. of the 7th International Semantic Web Conference, Karlsruhe, Germany, pp.178-194, 2008.
    D.M. Li, Y.F. Lin, H.K. Huang and X. Tian, "Measuring ontology inconsistency based on Dempster-Shafer theory", Journal of Computer Research and Development, Vol.50, No.3, pp.559- 567, 2013. (in Chinese)
    D.M. Li, Y.F. Lin, H.K. Huang, S.D. Hao and J.X. Wang, "Dempster-Shafer inconsistency values", Chinese Journal of Electronics, Vol.23, No.2, pp.227-231, 2014.
    J. Wang, E.H. Chen, D.M. Shi and Z.Y. Zhang, "Semantic similarity-based information retrieval method", PR & AI, Vol.19, No.6, pp.696-701, 2006. (in Chinese)
    Y.H. Yang, J.P. Du and B.W. He, "A novel ontology-based semantic retrieval model for food safety domain", Chinese Journal of Electronics, Vol.22, No,2, pp.247-252, 2013.
    M. Strube and S.P. Ponzetto, "WikiRelate! Computing semantic relatedness using Wikipedia", Proc. of the 21st National Conference on Artificial Intelligence (AAAI'06), Boston, USA, pp.1419-1424, 2006.
    E. Gabrilovich and S. Markovitch, "Computing semantic relatedness using Wikipedia-based explicit semantic analysis", IJCAI, Vol.7, No.1, pp.1606-1611, 2007.
    M.V. Assem, M.R. Menken, G. Schreiber, J. Wielemaker and B. Wielinga, "A method for converting thesauri to RDF/OWL", Proc. of the Third International Semantic Web Conference, Hiroshima, Japan, pp.17-31, 2004.
    J.X. Huang, J.A. Shin and K.S. Choi, "Enriching core ontology with domain thesaurus through concept and relation classification", Proc. of the sixth International Semantic Web Conference, Busan, South-Korea, pp.1-10, 2007.
    D. Sánchez, M. Batet, D. Isern, et al., "Ontology-based semantic similarity: A new feature-based approach", Expert Systems with Applications, Vol.39, No.9, pp.7718-7728, 2012.
    Q. Liu and S.J. Li, "Word similarity computing based on Hownet", Proc. of the 3rd Chinese Lexical Semantic Workshop, Taipei, 2003. (in Chinese)
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (178) PDF downloads(569) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint