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Biologically Inspired Linguistic Habit Graph Networks Used for Text Correction

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Recent Developments and Achievements in Biocybernetics and Biomedical Engineering (PCBBE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 647))

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Abstract

This paper describes a biologically inspired Linguistic Habit Graphs (LHG) which could be used as a new way of storing, compressing, and processing sentences. The common letter and word orders from sentences are used to construct a special neural graph that is able to associate and memorize the natural human linguistic habits. The used algorithms can learn from texts written by people and transform the information of orders, frequencies, and contexts into a graph structure, labeled vertices with word properties, and weighted connections. Vertices of this graph are reactive to input data as well as neurons in biological brains. The way in which the human brain works is an inspiration for many known algorithms from contemporary computer science. In the brain, there is no time and no place for nested loops and other time consuming classic algorithms and computational techniques. Based on this approach, we developed new algorithms. They use a graph structure to perform a semi–automatic spell checking and text correction. The above mentioned functionalities of this model are always available in constant time.

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Acknowledgments

This research was supported by AGH 11.11.120.612.

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Authors and Affiliations

  1. AGH University of Science and Technology, Department of Automatics and Biomedical Engineering, Mickiewicza Av. 30, 30–059, Krakow, Poland

    Marcin Gadamer & Adrian Horzyk

Authors
  1. Marcin Gadamer
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  2. Adrian Horzyk
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Corresponding author

Correspondence to Marcin Gadamer .

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Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Piotr Augustyniak

  2. Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

    Roman Maniewski

  3. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

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Gadamer, M., Horzyk, A. (2018). Biologically Inspired Linguistic Habit Graph Networks Used for Text Correction. In: Augustyniak, P., Maniewski, R., Tadeusiewicz, R. (eds) Recent Developments and Achievements in Biocybernetics and Biomedical Engineering. PCBBE 2017. Advances in Intelligent Systems and Computing, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-319-66905-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-66905-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66904-5

  • Online ISBN: 978-3-319-66905-2

  • eBook Packages: EngineeringEngineering (R0)

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