Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Semantic learning is an important mechanism for the document classification, but most classification approaches are only considered the content and words distribution. Traditional classification algorithms cannot accurately represent the meaning of a document because it does not take into account semantic relations between words. In this paper, we present an approach for classification of documents by incorporating two similarity computing score method. First, a semantic similarity method which computes the probable similarity based on the Bayes’ method and second, n-grams pairs based on the frequent terms probability similarity score. Since, both semantic and Ngrams pairs can play important roles in a separated views for the classification of the document, we design a semantic similarity learning (SSL) algorithm to improves the performance of document classification for a huge quantity of unclassified documents.
V Vineeth Kumar. 2017. \u201cProbability of Semantic Similarity and N-grams Pattern Learning for Data Classification\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 17 (GJCST Volume 17 Issue H2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Semantic learning is an important mechanism for the document classification, but most classification approaches are only considered the content and words distribution. Traditional classification algorithms cannot accurately represent the meaning of a document because it does not take into account semantic relations between words. In this paper, we present an approach for classification of documents by incorporating two similarity computing score method. First, a semantic similarity method which computes the probable similarity based on the Bayes’ method and second, n-grams pairs based on the frequent terms probability similarity score. Since, both semantic and Ngrams pairs can play important roles in a separated views for the classification of the document, we design a semantic similarity learning (SSL) algorithm to improves the performance of document classification for a huge quantity of unclassified documents.
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