Research on an Agricultural Knowledge Fusion Method for Big Data

Authors

  • Nengfu Xie Key Laboratory of Digital Agricultural Early-Warning Technology, Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
  • Wensheng Wang Key Laboratory of Digital Agricultural Early-Warning Technology, Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
  • Bingxian Ma School of Information Science and Engineering, University of Jinan, Jinan 250022
  • Xuefu Zhang Key Laboratory of Digital Agricultural Early-Warning Technology, Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
  • Wei Sun Key Laboratory of Digital Agricultural Early-Warning Technology, Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
  • Fenglei Guo Key Laboratory of Digital Agricultural Early-Warning Technology, Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081

DOI:

https://doi.org/10.5334/dsj-2015-007

Keywords:

Ontology, Big data, Agriculture, Knowledge fusion, Information integration, Inconsistency

Abstract

The object of our research is to develop an ontology-based agricultural knowledge fusion method that can be used as a comprehensive basis on which to solve agricultural information inconsistencies, analyze data, and discover new knowledge. A recent survey has provided a detailed comparison of various fusion methods used with Deep Web data (Li, 2013). In this paper, we propose an effective agricultural ontology-based knowledge fusion method by leveraging recent advances in data fusion, such as the semantic web and big data technologies, that will enhance the identification and fusion of new and existing data sets to make big data analytics more possible. We provide a detailed fusion method that includes agricultural ontology building, fusion rule construction, an evaluation module, etc. Empirical results show that this knowledge fusion method is useful for knowledge discovery.

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Published

2015-05-22

Issue

Vol. 14 (2015)

Section

Proceedings Papers

License

Copyright (c) 2015 The Author(s)

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