Relevance of a Set of Topical Texts to a Knowledge Unit and the Estimation of the Closeness of Linguistic Forms of Its Expression to a Semantic Pattern

Author:

Emelyanov G. M.,Mikhailov D. V.,Kozlov A. P.

Publisher

Pleiades Publishing Ltd

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition

Reference11 articles.

1. D. V. Mikhaylov, A. P. Kozlov, and G. M. Emelyanov, “An approach based on TF–IDF metrics to extract the knowledge and relevant linguistic means on subjectoriented text sets,” Comput. Opt. 39 (3), 429–438 (2015) [in Russian].

2. D. V. Mikhaylov, A. P. Kozlov, and G. M. Emelyanov, “An approach based on analysis of n–grams on links of words to extract the knowledge and relevant linguistic means on subject–oriented text sets,” Comput. Opt. 41 (3), 461–471 (2017) [in Russian].

3. G. M. Emelyanov, D. V. Mikhaylov, and A. P. Kozlov, “Formation of the representation of topical knowledge units in the problem of their estimation on the basis of open tests,” Mash. Obuch. Anal. Dannykh (Mach. Learn. Data Anal.) 1 (8), 1089–1106 (2014) [in Russian].

4. E. Huang, “Paraphrase detection using recursive autoencoder,” Stanford NLP Group, Natural Language Processing, Final Projects Reports (Stanford University, Stanford, CA, 2011). Available at: http://nlp.stanford. edu/courses/cs224n/2011/reports/ehhuang.pdf

5. MaltParser: A Data–Driven Dependency Parser. Available at http://www.maltparser.org/

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