Research on an Agricultural Knowledge Fusion Method for Big Data

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 variou...

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Bibliographic Details
Main Authors: Nengfu Xie, Wensheng Wang, Bingxian Ma, Xuefu Zhang, Wei Sun, Fenglei Guo
Format: Article
Language:English
Published: Ubiquity Press 2015-05-01
Series:Data Science Journal
Subjects:
Online Access:http://datascience.codata.org/articles/559
Description
Summary: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.
ISSN:1683-1470