Szczegóły publikacji
Opis bibliograficzny
Linguistic Habit Graphs used for text representation and correction / Marcin GADAMER // W: Artificial Intelligence and Soft Computing : 16th International Conference : ICAISC 2017 Zakopane, Poland, June 11–15, 2017 : proceedings, Pt. 2 / eds. Leszek Rutkowski, [et al.]. — Switzerland : Springer International Publishing, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; LNAI 10246). — Toż na Dysku Flash. — ISBN: 978-3-319-59059-2; e-ISBN: 978-3-319-59060-8. — S. 233–242. — Bibliogr. s. 241–242, Abstr.
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 106576 |
|---|---|
| Data dodania do BaDAP | 2017-06-30 |
| DOI | 10.1007/978-3-319-59060-8_22 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Artificial Intelligence and Soft Computing 2017 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
This paper introduces a novel associative way of storing, compressing, and processing sentences. The Linguistic Habit Graphs (LHG) are introduced as graph models that could be used for spell checking, text correction, proof–reading, and compression of sentences. All the above mentioned functionalities are always available in the constant computational complexity as a result of the associative way of text processing, special kinds of connections and graph nodes that enable to activate various important relations between letters and words simultaneously for any given contexts. Furthermore, using the proposed graph structure, new algorithms have been developed to provide effective text analyzes and contextual text correction. These new algorithms can properly locate and often automatically correct typical mistakes in texts written in a given language for which the graph was build.
