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A Recommend Method of Hotspots Knowledge Based on Big Data from Evolving Network

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Computational Intelligence and Intelligent Systems (ISICA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 873))

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Abstract

Because of the rapid growth of all kinds of professional knowledge on the internet. There are three characteristics about the big data in the Internet: the amount of information is huge, the type of information is changing quickly, the requirements of people are diverse. How to help users discover hotspots knowledge to meet their personalized are becomes a challenging and hot issue. Thus, in this paper, we propose the evolving network combine with word2vec. To address this issue. first, we construct the evolving network and analyze the data relationships based on Wikipedia knowledge tree and software engineering open source community (e.g., Stack Overflow) in real time; second, the evolving network can merge similarity and synonym of hotspots terms by Word2vec. Finally, we can calculate the weight of each hotspots, the nodes with the greatest weight in each domain are recommend knowledge. We evaluated stability, recall rate, precision rate, and F-Measure through an experiment and the results showed that our method is more accurate than existing approaches.

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Acknowledgements

This work was supported in part by the National Key Research and Development Programs of China (2016YFC0802503, 2016YFB0800403), by the PI Project of Hubei Provincial Collaborative Innovation Center for New Energy Microgrid (CTGU) (8006116), by the Open Foundation of Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering (2015KLA03), and by the Open Foundation of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area (Ministry of Education) (2015KDZ05).

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Authors and Affiliations

  1. Computer School of Wuhan University, Wuhan, 430072, China

    Yi Zhao

  2. China Three Gorges University, Yichang, 443002, China

    Zhao Li & Jun Wu

Authors
  1. Yi Zhao
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  2. Zhao Li
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  3. Jun Wu
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Corresponding author

Correspondence to Zhao Li .

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Editors and Affiliations

  1. College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China

    Wei Li

  3. Chemical and Petroleum Engineering, University of Calgary, Calgary, Alberta, Canada

    Zhangxing Chen

  4. School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

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Zhao, Y., Li, Z., Wu, J. (2018). A Recommend Method of Hotspots Knowledge Based on Big Data from Evolving Network. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 873. Springer, Singapore. https://doi.org/10.1007/978-981-13-1648-7_40

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  • DOI: https://doi.org/10.1007/978-981-13-1648-7_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1647-0

  • Online ISBN: 978-981-13-1648-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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