KeyStract is a method designed for keyphrase extraction from a single document (Pasquier 2010). The principle of the algorithm is to cluster sentences of the documents in order to highlight parts of text that are semantically related. The clusters of sentences, that reflect the themes of the document, are then analyzed to find the main topics of the text. Finally, the most important words, or groups of words, from these topics are proposed as keyphrases. This method has been evaluated on task number 5 (Automatic Keyphrase Extraction from Scientific Articles) of SemEval-2010: the 5th International Workshop on Semantic Evaluations.
Pasquier, C. (2010), “Single Document Keyphrase Extraction Using Sentence Clustering and Latent Dirichlet Allocation,” in 5th international workshop on semantic evaluation, semeval 2010 (acl’10), Uppsala: Association for Computational Linguistics, pp. 154–157.