Construction and Recommendation of a Water Affair Knowledge Graph

Jianzhuo Yan, Tiantian Lv and Yongchuan Yu
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Jianzhuo Yan: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Tiantian Lv: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Yongchuan Yu: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

Sustainability, 2018, vol. 10, issue 10, 1-15

Abstract: Water affair data mainly consists of structured data and unstructured data, and the storage methods of data are diverse and heterogeneous. To meet the needs of water affair information integration, a method of constructing a knowledge graph using a combination of water affair structured and unstructured data is proposed. To meet the needs of a water information search, an information recommendation system for constructing a water affair knowledge graph is proposed. In this paper, the edit distance algorithm and latent Dirichlet allocation (LDA) algorithm are used to construct a water affair structured data and unstructured data combination knowledge graph, and this graph is validated based on the semantic distance algorithm. Finally, this paper uses the recall rate, accuracy rate, and F comprehensive results to compare the algorithms. The evaluation results of the edit distance algorithm and the LDA algorithm exceed 90%, which is greater than the comparison algorithm, thus confirming the validity and accuracy of the construction of a water affair knowledge graph. Furthermore, a set of water affair verification sets is used to verify the recommendation method, which proves the effectiveness of the recommended method.

Keywords: structured data; unstructured data; water affair; knowledge graph construction; information recommendation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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