Keyword assignment methods can be roughly divided into:
Methods for automatic keyword extraction can be supervised, semi-supervised, or unsupervised.4 Unsupervised methods can be further divided into simple statistics, linguistics or graph-based, or ensemble methods that combine some or most of these methods. 5
Beliga, Slobodan; Ana, Meštrović; Martinčić-Ipšić, Sanda. (2015). "An Overview of Graph-Based Keyword Extraction Methods and Approaches". Journal of Information and Organizational Sciences. 39 (1): 1–20. http://hrcak.srce.hr/file/207669 ↩
Rada Mihalcea; Paul Tarau (July 2004). TextRank: Bringing Order into Texts (PDF). Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2004). Barcelona, Spain. http://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf ↩
Beliga, Slobodan; Meštrović, Ana; Martinčić- Ipšić, Sanda. (2014). Toward Selectivity-Based Keyword Extraction for Croatian News (PDF). Surfacing the Deep and the Social Web (SDSW 2014). Vol. 1310. Italy: CEUR Proc. pp. 1–14. http://ceur-ws.org/Vol-1310/paper1.pdf ↩
Alrehamy, H.; Walker, C. (2017). SemCluster: Unsupervised Automatic Keyphrase Extraction Using Affinity Propagation. 17th UK Workshop on Computational Intelligence. https://www.researchgate.net/publication/318436236 ↩
Tayfun Pay; Stephen Lucci (2017). Automatic Keyword Extraction: An Ensemble Method. 2017 IEEE International Conference on Big Data (Big Data). doi:10.1109/BigData.2017.8258552. /wiki/Doi_(identifier) ↩