Vol.7, No.4, November 2018.                                                                                                                                                                             ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

TEM Journal

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science

A Step toward Machine Recognition of Complex Sentences

Marko Orešković, Juraj Benić, Mario Essert

© 2018 Marko Orešković, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

Citation Information: TEM Journal. Volume 7, Issue 4, Pages 823-828, ISSN 2217-8309, DOI: 10.18421/TEM74-20, November 2018.

Received: 04 September 2018.
Accepted: 06 November 2018.
Published: 26 November 2018.

Abstract:

Abstract – This paper presents theoretical and technological background of a model for machine recognition of complex sentences. It is based on the
Syntactic and Semantic Framework (SSF) which implements fundamental linguistic fields network resources and encyclopedias. It can be used to extract
subject, predicate and object, as well as other sentence's parts (e.g. NP/VP/PP), and in some cases even semantic roles. In compound sentences the
machine can easily recognize independent sentences, whereas in complex sentences the machine recognizes the main clause and the related subordinate clauses as well as sentence types (subject, object, predicate, etc.). Using stored patterns various theories can be tested.

Keywords –complex and compound sentences, machine recognition, syntactic patterns, frequency analysis, computer model.

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