Funder
Innovation Fund for University Production, Education and Research from China’s Ministry of Education
National Natural Science Foundation of China
International Exchange Program for Graduate Students, Tongji University
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Computer Science Applications,General Social Sciences
Reference54 articles.
1. Abilhoa, W. D., & De Castro, L. N. (2014a). A keyword extraction method from twitter messages represented as graphs. Applied Mathematics and Computation,240, 308–325.
2. Abilhoa, W. D., & De Castro, L. N. (2014b). TKG: A graph-based approach to extract keywords from tweets. In Distributed computing and artificial intelligence, 11th International Conference (pp. 425–432). Cham: Springer.
3. Azad, H. K., & Deepak, A. (2019). Query expansion techniques for information retrieval: A survey. Information Processing and Management,56(5), 1698–1735.
4. Beliga, S., Meštrović, A., & Martinčić-Ipšić, S. (2015). An overview of graph-based keyword extraction methods and approaches. Journal of information and organizational sciences,39(1), 1–20.
5. Biswas, S. K., Bordoloi, M., & Shreya, J. (2018). A graph based keyword extraction model using collective node weight. Expert Systems with Applications,97, 51–59.
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