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Journal of Computer Technology & Applications Cover

Journal of Computer Technology & Applications

E-ISSN: 2229-6964 | P-ISSN: 2347-7229 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

Journal of Computer Technology & Applications [2229-6964(e)] is a peer-reviewed hybrid open-access journal launched in 2010, focused on the rapid publication of fundamental research papers in all areas concerning the latest and recent research and review work in computers and their commercial … and research contributions.

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Journal Metrics

Key performance indicators showcasing our journal’s impact and reach

89

Published Articles (2024)

47.61

Days Acceptance Time

84.51

Day Publication Time

—

Total Visits

Journal Information

Title: Journal of Computer Technology & Applications
Abbreviation: jocta
Issues Per Year: 3 Issues
P-ISSN: 2347-7229
E-ISSN: 2229-6964
Publisher: STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI: 10.37591/JOCTA
Starting Year: 2010
Publication Format: Hybrid Open Access
Language: English
Copyright Policy: CC BY-NC-ND
Type: Peer-reviewed Journal (Refereed Journal)

Address:

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin - 201301

Editorial Board

View Full Editorial Board

jocta maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Varsha Kiran Bhosale, Associate Professor

Dnyanshree Institute of Engineering and Technology, Maharashtra, India, 415013

Email :

Latest Articles

Ahead of Print

Deep Learning Approaches for Graph Similarity Computation: A Review

Graph-structured data is increasingly prevalent in many real-world applications such as social networks, biological systems, molecular chemistry, and knowledge graphs.

Graph Similarity, Graph Neural Networks, Graph Matching, Graph Representation Learning, Deep Learning on Graphs, Knowledge Graph Alignment, Graph Embedding, Geometric Deep Learning

A SHAP-Enhanced Voice-Based Conversational Agent for Agriculture Using BERT

The integration of advanced artificial intelligence technologies into modern agriculture has become increasingly important for narrowing the persistent knowledge gap faced by farmers, especially in regions with limited access to expert advisory services.

Agriculture, BERT, conversational agent, explainable AI (XAI), natural language processing (NLP), SHAP, voice interface

AI-Based Machine Learning Web Application Firewall (ML-WAF)

This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security.

AI, deep learning, HTTP traffic, machine learning, web application firewall, XSS

AI-Augmented Online Aptitude Exam System with Adaptive Testing, Intelligent Question Generation and Performance Analytics

In the non-technological world, assessment is inflexible, catering for the diverse ability range of test takers which automatically leads to sub-optimal assessment, and sub-optimal engagement with the assessment.

Adaptive testing, item response theory, educational assessment, machine learning classifiers, BERT, performance analytics, real-time systems, educational technology

Insurance Chatbot for Customer Support Using LLM and Generative AI

The Insurance Chatbot for Customer Support is an AI inspired solution designed to streamline customer interactions within the insurance industry.

AI-powered chatbot, large language models (LLMs), generative AI, natural language processing (NLP), LangServe, LangSmith

Feature Engineering in Modern Predictive Modeling: Techniques, Automation Frameworks and Emerging Trends

Feature engineering plays a crucial role in developing reliable and high-performing predictive models.

Graph neural networks, AutoML, feature tools, SHAP, federated learning, feature engineering
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