The research document corpses grow with more and more publication in the various field of research. Keywords play an important role in grouping these documents and making it available to users. This paper gives an insight into the new emerging and ongoing models of keyword extraction. Here we have explained four new different ways for keyword extraction, that are TF-IDF, sentence embedding and graph-based models. In which graph-based models for extraction of keywords contain two different ways that are, by collective node weight and by building the graph. And in TF-IDF it shows the comparison of five different combinations of frequency measurement for extraction of keywords. These keyword extraction techniques are unsupervised methods. An unsupervised method does not need any input data other than the document itself for extracting keywords.
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