LIU Jie, LI Wei, LUO Liming, ZHOU Jianshe, HAN Xu, SHI Jinsheng. Linked Open Data Query Based on Natural Language[J]. Chinese Journal of Electronics, 2017, 26(2): 230-235. doi: 10.1049/cje.2016.11.003
Citation: LIU Jie, LI Wei, LUO Liming, ZHOU Jianshe, HAN Xu, SHI Jinsheng. Linked Open Data Query Based on Natural Language[J]. Chinese Journal of Electronics, 2017, 26(2): 230-235. doi: 10.1049/cje.2016.11.003

Linked Open Data Query Based on Natural Language

doi: 10.1049/cje.2016.11.003
Funds:  This work is supported by Beijing Advanced Innovation Center for Imaging Technology, the National Natural Science Foundation of China (No.61371194, No.61672361), Beijing Natural Science Foundation (No.4152012), and Beijing city Key construction discipline "Computer Application Technology".
More Information
  • Corresponding author: LUO Liming (corresponding author) was born in 1963. He received M.S. degree in Capital Normal University. His main research interests include Semantic Web, Construction of Software System and Intelligent Education, etc. (Email:luolm@cnu.edu.cn.)
  • Received Date: 2016-03-21
  • Rev Recd Date: 2016-04-20
  • Publish Date: 2017-03-10
  • Linked open data (LOD) supports the SPARQL query strongly. A translation system from the natural language query to the SPARQL query based on the syntax rules is proposed. For a natural language query, a parsing method is proposed to represent the query intention and construct the corresponding query graph. The algorithms for obtaining and instantiating triple patterns are designed based on the rules. A mapping method for different types of graph nodes is lastly proposed to improve the recall. The experiments based on test data from QALD-4 are conducted. Compared with the other systems, our system is more easy and effective, and evaluation results are outstanding in the field of unsupervised learning.
  • loading
  • C. Bizer, T. Heath and T. Berners-Lee, "Linked Data the story so far", International Journal on Semantic Web and Information Systems, Vol.5, No.3, pp.1-22, 2009.
    S. Auer, C. Bizer, G. Kobilarov, et al., "DBpedia:A nucleus for a web of open data", Proc. of the 6th International Semantic Web Conference Busan, Korea, pp.11-15, 2007.
    F.M. Suchanek, G. Kasneci and G. Weikum, "Yago:A core of semantic knowledge unifying WordNet and Wikipedia", International World Wide Web Conference, Banff, Alberta, Canada pp.697-706, 2007.
    J. Perez, M. Arenas and C. Gutierrez, "Semantics and complexity of SPARQL", ACM Transactions on Database Systems Vol.34, No.3, pp.30-43, 2009.
    X.I. Ning, X. Dai, S. Huang, et al., "Discriminative word alignment over multiple word segmentations", Chinese Journal of Electronics, Vol.23, No.2, pp.263-270, 2014.
    C. Dima, "Answering natural language questions with Intui3", CLEF 2014 Working Notes Papers, Sheffield, UK, pp.1201-1211, 2014.
    S. Park, H. Shim and G.G. Lee, "ISOFT at QALD-4:Semantic similarity-based question answering system over linked data", CLEF 2014 Working Notes Papers, Sheffield, UK, pp.1236-1248, 2014.
    C. Unger, L. Buhmann, J. Lehmann, et al., "Template-based question answering over RDF data", International Conference on World Wide Web, New York, USA pp.639-648, 2012.
    C. Pradel, G. Peyet, O. Haemmerle, et al., "SWIP at QALD-3:results, criticisms and lesson learned", the 3rd Open Challenge on Question Answering over Linked Data (QALD 2013), Valencia, Spain, pp.1-13, 2013.
    K. Xu, S. Zhang, Y. Feng, et al., "Answering natural language questions via phrasal semantic parsing", Proc. of Natural Language Processing and Chinese Computing, Shenzhen, China, pp.333-344, 2014.
    S. He, Y Zhang, L. Kang, et al., "CASIA@V2:A MLN-based question answering system over linked data", CLEF 2014 Working Notes Papers, Sheffield, UK, pp.1249-1259, 2014.
    L. Zou, R. Huang, H. Wang, et al., "Natural language question answering over RDF:A graph data driven approach", Proc. of the 2014 ACM SIGMOD International Conference on Management of Data, New York, USA, pp.313-324, 2014.
    J.R. Finkel, T. Grenager and C. Manning, "Incorporating non-local information into information extraction systems by Gibbs sampling", Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, Stroudsburg, Pennsylvania, USA, pp.363-370, 2005.
    D. Lin, "An information-theoretic definition of similarity", Proc. of fifteenth International Conference on Machine Learning, San Francisco, California, USA, pp.296-304, 1998.
    C. Unger, "Multilingual Question Answering over Linked Data:QALD-4 Dataset", https://pub.uni-bielefeld.de/data/2687439, 2016-3-21.
    C. Unger, C. Forascu, V. Lopez, et al., "Question Answering over Linked Data (QALD-4)", CLEF 2014 Working Notes Papers, Sheffield, UK, pp.1172-1180, 2014.
  • 加载中

Catalog

    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 (169) PDF downloads(903) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return