Concepts Identification in Large Scale Datasets for Efficient Text Categorization

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Y. Sri Lalitha, Lohitha Bhogapati

Abstract

Concept Based Document removal is an increasing modern Research with the intention of activities in the direction of gather important in sequence as of normal words processing term. It might be there uncertainly eminent because the path of investigative texts toward takes out in sequence with the intention to be realistic happening exacting purposes. In this case, the mining representation capable of detain provisions that identify the concepts of the ruling or document, which tends toward notice the theme of the document. In an vacant job, the concept-based taking out representation be utilized merely intended for usual transcript credentials clustering in accumulation to clustered the transcript parts of the credentials in count to capably discovers important the same concepts between credentials, according toward the semantics sentence. however the negative aspect of the job be with the intention of the accessible job cannot subsist connected toward net credentials clustering along with the transcript categorization intended for the credentials be an undependable lone. Concept-Based drawing out representation used for attractive transcript Clustering.

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How to Cite
Y. Sri Lalitha, Lohitha Bhogapati. (2023). Concepts Identification in Large Scale Datasets for Efficient Text Categorization . Turkish Journal of Computer and Mathematics Education (TURCOMAT), 9(3), 766–775. https://doi.org/10.17762/turcomat.v9i3.13295
Section
Research Articles