Research on Search Intent Prediction for Big Data of National Grid System Standards
Authors: 
Hu Xueyong, Wang Bei, Zhao Lei, Yang Yang, Hu Aiyu, Pan Ge, Zhou BaoxianAuthors Info & Claims
Pages 89 - 93
Abstract
Smart grids are becoming more complex due to the development of big data., and technical documents and institutional standards are constantly updated. As a result, It is difficult for workers in different positions to obtain the required information and data. This thesis is oriented towards this problem, and combined with deep learning algorithms to build a user intent prediction model based on the existing knowledge map. By extracting user characteristics and using a dynamic matching algorithm, the purpose of intent prediction is achieved. In this way, the required standards and requirements can be found faster and more directly in the work process, which effectively improves the working efficiency of employees and reduces the difficulty of learning and training.
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Index Terms
- Research on Search Intent Prediction for Big Data of National Grid System Standards
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Published In
April 2020
563 pages
ISBN:9781450377089
DOI:10.1145/3404555
Copyright © 2020 ACM.
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- University of Tsukuba: University of Tsukuba
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 August 2020
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- Refereed limited
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ICCAI '20
ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence
April 23 - 26, 2020
Tianjin, China
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