A Semantic Significantly Improved Vector Space Model for Text Classification using Progressive Learning Network Algorithm

Registration ID: IJNRD_220559

Published ID: IJNRD2405105

DOI: Click Here to Get

Gopesh M , Dinesh Bala S , Rachagolla Likhith , Rajesh K

With digital data being increased on the internet, the text classification has become a very important thing. Text classification is a fundamental task in natural language processing (NLP) with applications in various domains such as sentiment analysis, document categorization, and spam detection. Even though the hierarchical classification stands best in classifying heterogenous data, Alternative Relative Discrimination (ARDC) has been proven as a better approach, which focuses on identifying terms frequently occurring in positive class. This paper presents a novel neural network-based technique for text classification which is optimized to mitigate existing text classification issues. We introduce improved Vector Space Model with Progressive Learning Network Algorithm (PLN). The current approach enhances traditional Vector Space Model by incorporating semantic information through advanced techniques such as word embeddings, contextual embeddings, and semantic similarity measures. This enriched representation enables the model to capture complex relationships and context dependencies within the text, leading to more accurate and nuanced classification results. Furthermore, we introduce the Progressive Learning Network algorithm, which facilitates continual learning and adaptation to new data without forgetting previously learned knowledge. By dynamically updating model parameters and representations over time, PLN ensures the adaptability and scalability of the SSIVSM in evolving text classification tasks.

Published Paper   E-Certificate

Gopesh M, Dinesh Bala S, Rachagolla Likhith, & Rajesh K (May-2024). A Semantic Significantly Improved Vector Space Model for Text Classification using Progressive Learning Network Algorithm . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), b35-b39. https://ijnrd.org/papers/IJNRD2405105.pdf

Volume 9 Issue 5, May-2024

Pages : b35-b39

Paper Reg. ID: IJNRD_220559

Published Paper Id: IJNRD2405105

Downloads: 000121978

Research Area: Computer Science & Technology 

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405105.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405105

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details