Proceedings of the 8th EAI International Conference on Green Energy and Networking, GreeNets 2021, June 6-7, 2021, Dalian, People’s Republic of China

Research Article

Keyword extraction and ranking based on crawler and natural language processing

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  • @INPROCEEDINGS{10.4108/eai.6-6-2021.2307707,
        author={Enbo  Zhang and Changmao  Li and Li  Liu},
        title={Keyword extraction and ranking based on crawler and natural language processing},
        proceedings={Proceedings of the 8th EAI International Conference on Green Energy and Networking, GreeNets 2021, June 6-7, 2021, Dalian, People’s Republic of China},
        publisher={EAI},
        proceedings_a={GREENETS},
        year={2021},
        month={8},
        keywords={crawler hidden markov model viterbi algorithm natural language},
        doi={10.4108/eai.6-6-2021.2307707}
    }
    
  • Enbo Zhang
    Changmao Li
    Li Liu
    Year: 2021
    Keyword extraction and ranking based on crawler and natural language processing
    GREENETS
    EAI
    DOI: 10.4108/eai.6-6-2021.2307707
Enbo Zhang1, Changmao Li1, Li Liu1,*
  • 1: Department of Information Science and Engineering Dalian Polytechnic University Dalian, P. R. China
*Contact email: link_liuli@hotmail.com

Abstract

This paper adopts crawler, Hidden Markov Model, Viterbi algorithm to make a segmentation of text data on Internet, and adopt TF-IDF algorithm to extract and sort the keywords. Secondly, an experiment was carried out to extract and sort keywords from analyzing online recruitment text data. Through the experience the authors come to the conclusions: The method described in this paper can analyze the keywords of the online text and apply to various situations.