Research Article
Keyword extraction and ranking based on crawler and natural language processing
@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
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.
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