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Neural Network Model for Semantic Analysis of Sanskrit Text

Author

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  • Smita Selot

    (Department of Computer Applications, SSTC, Bhiali, India)

  • Neeta Tripathi

    (SSTC, Bhiali, India)

  • A. S. Zadgaonkar

    (CV Raman University, Bilaspur, India)

Abstract

Semantic analysis is the process of extracting meaning of the sentence, from a given language. From the perspective of computer processing, challenge lies in making computer understand the meaning of the given sentence. Understandability depends upon the grammar, syntactic and semantic representation of the language and methods employed for extracting these parameters. Semantics interpretation methods of natural language varies from language to language, as grammatical structure and morphological representation of one language may be different from another. One ancient Indian language, Sanskrit, has its own unique way of embedding syntactic information within words of relevance in a sentence. Sanskrit grammar is defined in 4000 rules by PaninI reveals the mechanism of adding suffixes to words according to its use in sentence. Through this article, a method of extracting meaningful information through suffixes and classifying the word into a defined semantic category is presented. The application of NN-based classification has improved the processing of text.

Suggested Citation

  • Smita Selot & Neeta Tripathi & A. S. Zadgaonkar, 2018. "Neural Network Model for Semantic Analysis of Sanskrit Text," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 7(1), pages 1-14, January.
    • Handle: RePEc:igg:jncr00:v:7:y:2018:i:1:p:1-14
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