https://irju.jdvu.ac.in/jspui/handle/123456789/2 2026-10-14T19:58:11Z 2026-10-14T19:58:11Z Anwar Islam https://irju.jdvu.ac.in/jspui/handle/123456789/10690 2026-10-14T08:25:13Z 2024-01-01T00:00:00Z

Title: Development of an english spell checker Authors: Anwar Islam Abstract: Spelling correction is an important part of modern word processing systems, helping to accurately interpret user input. This thesis explores the development of a contextual, edit distance corrector built on foundational computational linguistics techniques. The work is organized around the noise channel model, a complex framework that corrects typographical errors by leveraging the likelihood of specific character permutations alongside prior word probabilities. Initially, we define practices and apply them to perform possible corrections for deletion, insertion, substitution errors, and transposition errors. This function is validated using English vocabulary definitions obtained from the NLTK corpus to ensure that candidate disciplines are properly English words. At the core of our spell corrector is a noise channel model, which combines possible typos with unigram probabilities derived from a large text corpus This model is enhanced by the inclusion of a bigram language model, which considers context around typos in a sentence to improve the accuracy of correction. Our approach includes constructing two grams of frequency cells and using Laplace smoothing to compute conditional probabilities. The final spelling correction task combines these possibilities to determine the most likely correction for a given typo by considering the noise channel and context. The analysis highlights the effectiveness of the system in correcting isolated words and spelling errors in sentences. However, it also highlights limitations, such as the need for extensive corpus data, the potential for contextual confusion in ambiguity. This thesis makes assumptions about of the development process and concludes with recommendations for future improvements to improve the accuracy and usability of the maintenance script This review contributes to a foundational understanding of the spelling correction tool and provides a practical application that balances simplicity and efficiency, and paves the way for advanced text processing and recognition tools the relevant information.

2024-01-01T00:00:00Z Robiul Islam https://irju.jdvu.ac.in/jspui/handle/123456789/10689 2026-10-14T08:21:14Z 2024-01-01T00:00:00Z

Title: Development of a question answer assessment webportal using django Authors: Robiul Islam Abstract: Question Answer Assessment Web Portal is a portal that provides an efficient, user-friendly way to conduct and manage assessments online. This web portal is a one stop unified solution to create, administer various types of exam and evaluate them as well which is developed on Django framework. Its wide range of functionality include everything that educators and students need; most importantly, it includes question banks, auto grading and performance analytics along with user management. This project aims at simplifying the process of assessment so that it can be easily employed and utilized by educational institutions. This system ensures strong feature set, scalable architecture, and security by using Django framework. It supports several roles like Admin, Teacher & Student with respective functions to provide a user-friendly environment. The goal of this project is to get above the limitations of both the existing online platforms and traditional paper examinations. It includes cutting-edge features including real-time feedback, several question types, and thorough performance reviews. To ensure dependability and user satisfaction, the creation process involved thorough requirement analysis, system design, and intensive testing. The initiative's results show a significant improvement in assessment effectiveness, and early users have responded favourably. More compatibility with various learning platforms and resources as well as AI-based analytics are among the upcoming improvements.

2024-01-01T00:00:00Z Muhuri, Subhajeet https://irju.jdvu.ac.in/jspui/handle/123456789/10688 2026-10-14T08:17:33Z 2024-01-01T00:00:00Z

Title: Development of an online question and answer management system using flask Authors: Muhuri, Subhajeet

2024-01-01T00:00:00Z Banerjee, Sayan https://irju.jdvu.ac.in/jspui/handle/123456789/10687 2026-10-14T08:11:24Z 2024-01-01T00:00:00Z

Title: Named entity recognition in bangla Authors: Banerjee, Sayan Abstract: Named Entity Recognition (NER) is a crucial task in natural language processing (NLP) that involves identifying and categorizing named entities within a body of text into predefined categories such as persons, organizations, locations, dates, and more. While substantial progress has been made in NER for high-resource languages like English, the development of NER systems for Bangla, a widely spoken language with complex morphology and syntax, remains challenging. In the context of the Bengali (Bangla) language, NER aims to extract and classify named entities specific to this linguistic and cultural context. The application of NER in Bangla is essential for numerous NLP tasks, including information extraction, question answering, and text summarization, which are particularly valuable for Bengali-speaking communities. Several challenges associated with Bangla language, which make NER a complex task. The language's morphological complexity and syntactic structure pose significant hurdles. Additionally, there is a scarcity of well-annotated datasets for Bangla NER. Variations in how named entities are represented in Bangla, such as different spellings and forms, further complicate the task. The development and effectiveness of Bangla NER systems largely depend on the availability of resources like labeled datasets, language models, and linguistic tools specifically designed for the Bangla. In this thesis, we are focusing on leveraging advanced deep learning models such as Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM) network, and BERT-based model. The aim is to improve the accuracy and reliability of NER systems in Bangla.

2024-01-01T00:00:00Z