Results for ' Natural Language Processing (NLP)'

43 found
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  1.  21
    UNDERSTANDING NATURAL LANGUAGE PROCESSING (NLP) TECHNIQUES: FROM TEXT ANALYSIS TO LANGUAGE GENERATION.Mittal Mohit - 2024 - International Journal of Research in Computer Applications and Information Technology 7 (2):2784-2792.
    This technical article explores the evolution and current state of Natural Language Processing (NLP), focusing on its fundamental components, sentiment analysis capabilities, language generation techniques, and implementation considerations. The article examines the transformation of NLP through transformer-based architectures, discussing advancements in text preprocessing, tokenization methods, and named entity recognition. It analyzes the progression of sentiment analysis from basic lexicon-based approaches to sophisticated neural architectures, highlighting improvements in contextual understanding and emotional context detection. The article also investigates (...)
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  2.  33
    Chatbot Assistant System _using Natural Language Processing (NLP) (7th edition).Prathamesh Shinde Rahul Rathod, - 2024 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 7 (11):17160-17164. Translated by Rahul Rathod.
    In the digital age, chatbots have emerged as essential tools for automating communication and improving user experiences across various sectors. This paper presents a Chatbot Assistant System powered by Natural Language Processing (NLP) to provide intelligent, context-aware, and real-time responses to user queries. The system incorporates NLP techniques, such as text preprocessing, intent recognition, and entity extraction, to facilitate effective interactions. We explore the architecture, working principles, and applications of the system, along with its performance evaluation in (...)
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  3. Ethical pitfalls for natural language processing in psychology.Mark Alfano, Emily Sullivan & Amir Ebrahimi Fard - forthcoming - In Morteza Dehghani & Ryan Boyd, The Atlas of Language Analysis in Psychology. Guilford Press.
    Knowledge is power. Knowledge about human psychology is increasingly being produced using natural language processing (NLP) and related techniques. The power that accompanies and harnesses this knowledge should be subject to ethical controls and oversight. In this chapter, we address the ethical pitfalls that are likely to be encountered in the context of such research. These pitfalls occur at various stages of the NLP pipeline, including data acquisition, enrichment, analysis, storage, and sharing. We also address secondary uses (...)
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  4. Operationalising Representation in Natural Language Processing.Jacqueline Harding - 2023 - British Journal for the Philosophy of Science.
    Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...)
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  5. OPTIMIZED CYBERBULLYING DETECTION IN SOCIAL MEDIA USING SUPERVISED MACHINE LEARNING AND NLP TECHNIQUES.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-435.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify (...)
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  6. Comparative Analysis of Deep Learning and Naïve Bayes for Language Processing Task.Olalere Abiodun - forthcoming - International Journal of Research and Innovation in Applied Sciences.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with (...)
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  7.  15
    Mining Customer Sentiments from Financial Feedback and Reviews using Data Mining Algorithms.Gopinathan Vimal Raja - 2021 - International Journal of Innovative Research in Computer and Communication Engineering 9 (12):14705-14710.
    Customer feedback and reviews are rich sources of information that reflect the sentiments and experiences of consumers, especially in the financial sector. Mining customer sentiments from these textual data sources provides valuable insights for improving services, identifying emerging issues, and predicting customer satisfaction. This paper proposes a novel approach to mining customer sentiments from financial feedback and reviews, leveraging advanced natural language processing (NLP) techniques, sentiment analysis algorithms, and machine learning models. We discuss methods for preprocessing financial (...)
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  8.  11
    Mining Customer Sentiments from Financial Feedback and Reviews using Data Mining Algorithms.Raja Gopinathan Vimal - 2021 - International Journal of Innovative Research in Computer and Communication Engineering 9 (12):14705-14710.
    Customer feedback and reviews are rich sources of information that reflect the sentiments and experiences of consumers, especially in the financial sector. Mining customer sentiments from these textual data sources provides valuable insights for improving services, identifying emerging issues, and predicting customer satisfaction. This paper proposes a novel approach to mining customer sentiments from financial feedback and reviews, leveraging advanced natural language processing (NLP) techniques, sentiment analysis algorithms, and machine learning models. We discuss methods for preprocessing financial (...)
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  9. Machine Learning-Based Cyberbullying Detection System with Enhanced Accuracy and Speed.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-429.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify (...)
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  10. Implementation and Comparison of Deep Learning with Naïve Bayes for Language Processing (4th edition).Abiodun Olalere - 2024 - Internation Journal of Research and Innovation in Appliad Science:1-6.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with (...)
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  11. Disease Identification using Machine Learning and NLP.S. Akila - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):78-92.
    Artificial Intelligence (AI) technologies are now widely used in a variety of fields to aid with knowledge acquisition and decision-making. Health information systems, in particular, can gain the most from AI advantages. Recently, symptoms-based illness prediction research and manufacturing have grown in popularity in the healthcare business. Several scholars and organisations have expressed an interest in applying contemporary computational tools to analyse and create novel approaches for rapidly and accurately predicting illnesses. In this study, we present a paradigm for assessing (...)
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  12. Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions.Flor Miriam Plaza-del-Arco, Alba Curry & Amanda Cercas Curry - forthcoming - Arxiv.
    Emotions are a central aspect of communication. Consequently, emotion analysis (EA) is a rapidly growing field in natural language processing (NLP). However, there is no consensus on scope, direction, or methods. In this paper, we conduct a thorough review of 154 relevant NLP publications from the last decade. Based on this review, we address four different questions: (1) How are EA tasks defined in NLP? (2) What are the most prominent emotion frameworks and which emotions are modeled? (...)
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  13. Speech Based Controlled Techniques using NLP.R. Senthilkumar - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):24-32.
    The main objective of our project is to construct a fully functional voice-based home automation system that uses the Internet of Things and Natural Language Processing. The home automation system is user-friendly to smartphones and laptops. A set of relays is used to connect the Node MCU to homes under controlled appliances. The user sends a command through the speech to the mobile devices, which interprets the message and sends the appropriate command to the specific appliance. The (...)
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  14. Software for Dubbing English Videos into Indian Languages.V. Deepak - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (1):1-13.
    In a country as linguistically diverse as India, the demand for localized video content is rapidly increasing. Dubbing English videos into Indian languages, such as Hindi, Tamil, Telugu, and Bengali, is critical to making content accessible to wider audiences. This paper presents a software solution that automates the dubbing process using a combination of technologies like Automatic Speech Recognition (ASR), Machine Translation (MT), andText-to-Speech (TTS). The process begins by converting English audio into text using ASR, followed by translation into the (...)
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  15.  12
    AI-Powered Phishing Detection: Protecting Enterprises from Advanced Social Engineering Attacks.Bellamkonda Srikanth - 2022 - International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 11 (1):12-20.
    Phishing, a prevalent form of social engineering attack, continues to threaten enterprises by exploiting human vulnerabilities and targeting sensitive information. With the increasing sophistication of phishing schemes, traditional detection methods often fall short in identifying and mitigating these threats. As attackers employ advanced techniques, such as highly personalized spear-phishing emails and malicious links, enterprises require innovative solutions to safeguard their digital ecosystems. This research explores the application of artificial intelligence (AI) in enhancing phishing detection and response, with a specific focus (...)
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  16.  57
    Advanced AI Algorithms for Automating Data Preprocessing in Healthcare: Optimizing Data Quality and Reducing Processing Time.Muthukrishnan Muthusubramanian Praveen Sivathapandi, Prabhu Krishnaswamy - 2022 - Journal of Science and Technology (Jst) 3 (4):126-167.
    This research paper presents an in-depth analysis of advanced artificial intelligence (AI) algorithms designed to automate data preprocessing in the healthcare sector. The automation of data preprocessing is crucial due to the overwhelming volume, diversity, and complexity of healthcare data, which includes medical records, diagnostic imaging, sensor data from medical devices, genomic data, and other heterogeneous sources. These datasets often exhibit various inconsistencies such as missing values, noise, outliers, and redundant or irrelevant information that necessitate extensive preprocessing before being analyzed (...)
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  17. Automated Cyberbullying Detection Framework Using NLP and Supervised Machine Learning Models.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-432.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify (...)
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  18. Are we at the start of the artificial intelligence era in academic publishing?Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Ruining Jin & Tam-Tri Le - 2023 - Science Editing 10 (2):1-7.
    Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making (...)
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  19.  56
    Granular Interaction Thinking Theory in Open Science: A Novel Approach for Enhancing the Plausibility of Social Sciences.Minh-Hoang Nguyen, Viet-Phuong La & Quan-Hoang Vuong - manuscript
    The reproducibility crisis in social sciences has revealed significant weaknesses in conventional research practices, including selective publication, questionable statistical methods, and opaque peer review processes. This paper introduces Granular Interaction Thinking Theory (GITT) as a novel framework for understanding the plausibility of scientific findings, conceptualizing knowledge validation as a structured entropy-reduction process. Within this framework, open science practices—such as open data, open review, and open dialogue—initially increase informational entropy by exposing inconsistencies. However, through iterative refinement, they ultimately enhance the robustness (...)
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  20.  46
    Empowering Communication for Indian Sign Language Users Through Ai-Driven Real-Time Translation.S. Kusum Choudhary - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (7):1-15.
    Indian Sign Language (ISL) users face challenges communicating effectively with English speakers, primarily due to a lack of accessible, real-time translation tools. Existing systems often struggle with context and natural flow, leading to misunderstandings and reduced usability. This project proposes an AI-powered system designed to overcome these limitations, incorporating speech recognition and natural language processing (NLP) to facilitate seamless interaction between ISL and English. The tool aims to bridge the language gap, providing ISL users (...)
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  21. Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3).Nassim Dehouche - 2021 - Ethics in Science and Environmental Politics 21:17-23.
    As if 2020 were not a peculiar enough year, its fifth month has seen the relatively quiet publication of a preprint describing the most powerful Natural Language Processing (NLP) system to date, GPT-3 (Generative Pre-trained Transformer-3), by Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial Beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this Artificial Intelligence (...)
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  22. A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.Yongqun He, Hong Yu, Anthony Huffman, Asiyah Yu Lin, Darren A. Natale, John Beverley, Ling Zheng, Yehoshua Perl, Zhigang Wang, Yingtong Liu, Edison Ong, Yang Wang, Philip Huang, Long Tran, Jinyang Du, Zalan Shah, Easheta Shah, Roshan Desai, Hsin-hui Huang, Yujia Tian, Eric Merrell, William D. Duncan, Sivaram Arabandi, Lynn M. Schriml, Jie Zheng, Anna Maria Masci, Liwei Wang, Hongfang Liu, Fatima Zohra Smaili, Robert Hoehndorf, Zoë May Pendlington, Paola Roncaglia, Xianwei Ye, Jiangan Xie, Yi-Wei Tang, Xiaolin Yang, Suyuan Peng, Luxia Zhang, Luonan Chen, Junguk Hur, Gilbert S. Omenn, Brian Athey & Barry Smith - 2022 - Journal of Biomedical Semantics 13 (1):25.
    The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...)
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  23. INTELLIGENT COMPUTING APPLICATIONS IN LINGUISTICS.Mohit Gangwar - 2024 - Rabindra Bharati Patrika (6):113-119.
    The intersection of intelligent computing and linguistics has emerged as a vibrant field of study, offering innovative solutions and applications that transform how we understand and interact with language. This paper explores the diverse applications of intelligent computing in linguistics, encompassing natural language processing (NLP), computational linguistics, language modeling, speech recognition, and more. It delves into the underlying technologies, methodologies, and the impact of these advancements on various linguistic subfields. Through an extensive review of recent (...)
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  24. Apropos of "Speciesist bias in AI: how AI applications perpetuate discrimination and unfair outcomes against animals".Ognjen Arandjelović - 2023 - AI and Ethics.
    The present comment concerns a recent AI & Ethics article which purports to report evidence of speciesist bias in various popular computer vision (CV) and natural language processing (NLP) machine learning models described in the literature. I examine the authors' analysis and show it, ironically, to be prejudicial, often being founded on poorly conceived assumptions and suffering from fallacious and insufficiently rigorous reasoning, its superficial appeal in large part relying on the sequacity of the article's target readership.
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  25.  57
    AYURMED.Bodla Chandana - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (3):1-12.
    Ayurvedic treatment, a traditional system of medicine, is valued for its individualized, and natural approach to health. Ayurvedic treatment encompasses a wide range of systems and practices designed to promote health and treat illness through holistic approaches. Existing solutions for Ayurvedic treatments include Ayur Times, Med9, and Jark Pharma. It includes diagnostic methods, various treatment modalities, and lifestyle recommendations. There are issues in the existing system, as in, the system lacks personalized recommendations, a user-friendly interface, and tailored filtering options. (...)
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  26. Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models.Christopher Grimsley, Elijah Mayfield & Julia Bursten - 2020 - Proceedings of the 12th Conference on Language Resources and Evaluation.
    As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this (...)
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  27.  84
    Deriving Insights and Financial Summaries from Public Data Using Large Language Models.Vijayan Naveen Edapurath - 2024 - International Journal of Innovative Research in Engineering and Multidisciplinary Physical Sciences 12 (6):1-12.
    This paper investigates how large language models (LLMs) can be applied to publicly available financial data to generate automated financial summaries and provide actionable recommendations for investors. We demonstrate how LLMs can process both structured financial data (balance sheets, income statements, stock prices) and unstructured text (earnings calls, management commentary) to derive insights, predict trends, and automate financial reporting. By focusing on a specific publicly traded company, this research outlines the methodology for leveraging LLMs to analyze company performance and (...)
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  28.  57
    Forecasting and Scheduling of Railway Rakes using Machine Learning.A. Pranay - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (7):1-15.
    Efficient rake scheduling and demand forecasting in railway operations are essential to address the complexities of passenger demand, minimize delays, and enhance utilization. This project uses advanced machine learning methods, specifically LSTM (Long Short-Term Memory) networks and GBM (Gradient Boosting Machine), to predict demand and optimize rake scheduling dynamically. Integrating a user-friendly web interface allows realtime data monitoring, enabling railway operators to make informed decisions. By leveraging real-time data sources, including rake movement, schedules, weather, and traffic conditions, this project aims (...)
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  29.  67
    Mining EU consultations through AI.Fabiana Di Porto, Paolo Fantozzi, Maurizio Naldi & Nicoletta Rangone - forthcoming - Artificial Intelligence and Law.
    Consultations are key to gather evidence that informs rulemaking. When analysing the feedback received, it is essential for the regulator to appropriately cluster stakeholders’ opinions, as misclustering may alter the representativeness of the positions, making some of them appear majoritarian when they might not be. The European Commission (EC)’s approach to clustering opinions in consultations lacks a standardized methodology, leading to reduced procedural transparency, while making use of computational tools only sporadically. This paper explores how natural language (...) (NLP) technologies may enhance the way opinion clustering is currently conducted by the EC. We examine 830 responses to three legislative proposals (the Artificial Intelligence Act, the Digital Markets Act and the Digital Services Act) using both a lexical and semantic approach. We find that some groups (like small and medium companies) have low similarity across all datasets and methodologies despite being clustered in one opinion group by the EC. The same happens for citizens and consumer associations for the consultation run over the DSA. These results suggest that computational tools actually help reduce misclustering of stakeholders’ opinions and consequently allow greater representativeness of the different positions expressed in consultations. They further suggest that the EC could identify a convergent methodology for all its consultations, where such tools are employed in a consistent and replicable rather than occasionally. Ideally, it should also explain when one methodology is preferred to another. This effort should find its way into the Better Regulation toolbox (EC 2023). Our analysis also paves the way for further research to reach a transparent and consistent methodology for group clustering. (shrink)
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  30.  51
    360-Degree Feedback Software for Government News Monitoring.Reddy Vanga Dinesh - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (8):1-16.
    News Rakshak is an advanced web application that monitors, analyzes, and verifies news related to government schemes in regional media across multiple platforms, including 200+ websites, e-papers, and YouTube channels. The application leverages Natural Language Processing (NLP) for sentiment analysis and integrates Artificial Intelligence (AI) to identify and flag fake news and videos. Sentiments are classified as positive, neutral, or negative, rated on a scale from 0 to 5, providing Public Information Bureau (PIB) officers with actionable insights. (...)
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  31. Tiến bộ công nghệ, AI: Kỷ nguyên số và an ninh thông tin quốc gia.Vương Quân Hoàng, Lã Việt Phương, Nguyễn Hồng Sơn & Nguyễn Minh Hoàng - manuscript
    Sự tiến bộ nhanh chóng của các nền tảng Công nghệ Thông tin (CNTT) và ngôn ngữ lập trình đã làm thay đổi hình thái vận động và phát triển của xã hội loài người. Không gian mạng và các tiện ích đi kèm ngày càng được mở rộng, dẫn đến sự chuyển dịch dần từ đời sống trong thế giới thực sang đời sống trong thế giới ảo (còn gọi là không gian mạng hay không gian số). Sự mở (...)
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  32. AI Driven Grievance Lodging and Tracking System.P. Raja Sekhar Reddy - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (3):1-12.
    The Grievance Management System is a web-based platform designed to enhance the efficiency and transparency of handling public grievances. By introducing role-based access for users, moderators, and government officials, the system ensures that grievances are systematically reviewed, prioritized, and resolved. Users can submit grievances, track their status, and receive notifications regarding updates. Moderators are tasked with verifying the validity of each grievance and assigning it a priority level before passing it on to government officials for action. Government officials, in turn, (...)
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  33. (3 other versions)Một số vấn đề an ninh thông tin trọng yếu trong kỷ nguyên AI (Phần 1: Tiến bộ công nghệ - Thách thức).Vương Quân Hoàng, Lã Việt Phương, Nguyễn Hồng Sơn & Nguyễn Minh Hoàng - 2024 - Hội Đồng Lý Luận Trung Ương.
    Sự tiến bộ nhanh chóng của các nền tảng Công nghệ Thông tin (CNTT) và ngôn ngữ lập trình đã làm thay đổi hình thái vận động và phát triển của xã hội loài người. Không gian mạng và các tiện ích đi kèm ngày càng được mở rộng, dẫn đến sự chuyển dịch dần từ đời sống trong thế giới thực sang đời sống trong thế giới ảo (còn gọi là không gian mạng hay không gian số). Sự mở (...)
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  34.  42
    Online Voting System_ using Machine Learning (13th edition).Shubham T. Borsare Vaishnavi D. Patil - 2025 - International Journal of Innovative Research in Computer and Communication Engineering 13 (1):1129-1131. Translated by Shubham T. Borsare Vaishnavi D. Patil.
    The increasing demand for secure and efficient voting systems has led to the exploration of online voting solutions. Traditional voting methods are often vulnerable to fraud, inefficiencies, and logistical challenges. This paper presents an online voting system that leverages machine learning techniques to enhance security, accuracy, and accessibility. The system employs facial recognition for voter authentication, anomaly detection to prevent fraudulent activities, and natural language processing (NLP) for user interaction. Experimental results indicate that the proposed model provides (...)
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  35. The use of situation theory in context modeling.Varol Akman & Mehmet Surav - 1997 - Computational Intelligence 13 (3):427-438.
    At the heart of natural language processing is the understanding of context dependent meanings. This paper presents a preliminary model of formal contexts based on situation theory. It also gives a worked-out example to show the use of contexts in lifting, i.e., how propositions holding in a particular context transform when they are moved to another context. This is useful in NLP applications where preserving meaning is a desideratum.
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  36.  40
    AI-Augmented Data Lineage: A Cognitive GraphBased Framework for Autonomous Data Traceability in Large Ecosystems.Pulicharla Dr Mohan Raja - 2025 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 8 (1):377-387.
    In the era of big data and distributed ecosystems, understanding the origin, flow, and transformation of data across complex infrastructures is critical for ensuring transparency, accountability, and informed decision-making. As data-driven enterprises increasingly rely on hybrid cloud architectures, data lakes, and real-time pipelines, the complexity of tracking data movement and transformations grows exponentially. Traditional data lineage solutions, often based on static metadata extraction or rule-based approaches, are insufficient in dynamically evolving environments and fail to provide granular, context-aware insights. This research (...)
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  37.  65
    Empowering Individuals with Disabilities: A Comprehensive Web Application for Job Training and Employment Support.G. Kartik Sarma - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (7):1-16.
    The "Udyog Saarthi App" is a progressive web-based application developed to enhance job coaching and career readiness for adults with disabilities, specifically focusing on the 4% reservation opportunities provided by NIEPMD and similar institutions in India. This innovative platform addresses the unique needs of users by allowing them to select their specific disability during registration, which customizes the website’s layout for improved accessibility. The application offers a comprehensive listing of real-time job opportunities that align with users' skills and qualifications, empowering (...)
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  38.  55
    Intelligent Classroom:Automated Audio-To-Notes Summarization System.Srinidhi Bhoopati - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (7):1-14.
    Students often struggle to capture accurate and comprehensive notes during lectures, which is crucial for effective learning. Traditional note-taking methods are time-consuming and prone to errors, especially when lectures include digressions or complex topics. Existing solutions, like manual transcription or basic audio recordings, fall short as they requireextensive post-processing and fail to structure information efficiently. This project proposes an automated Audio-to-Notes Summarization System that converts classroom audio into concise, structured notes. By leveraging advanced speech recognition, Natural Language (...)
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  39.  53
    An Autonomous AI Framework for Identifying Cognitive Concerns in Real-World Data.Priyanka S. Nidhi G. T. - 2024 - International Journal of Innovative Research in Computer and Communication Engineering 12 (12):14886-14889.
    The early detection of cognitive concerns is crucial for timely intervention and improved patient outcomes. However, analyzing large-scale real-world data for cognitive decline presents significant challenges in efficiency and accuracy. This paper introduces an Autonomous AI Framework that leverages machine learning and natural language processing (NLP) to identify cognitive concerns from diverse datasets, including electronic health records (EHRs), social media interactions, and clinical notes. Our approach integrates deep learning models, feature selection techniques, and interpretability methods to enhance (...)
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  40.  49
    Beyond the Claims: Emerging AI Models and Predictive Analytics in Property & Casualty Insurance Risk Assessment.Adavelli Sateesh Reddy - 2024 - International Journal of Science and Research 13 (7):1625-1631.
    P&C insurers have an important role in addressing financial risk management needs but now struggle to respond to the new forms of risk. Historical analysis and actuarial calculations, which form the backbone of classical approaches to risk measurement and management, are not well suited to such new kinds of risks as climate change, cyber risks, and business cycle risks. These conventional approaches are also a static method for selling, which has limited potential in changing quickly with new market and consumer (...)
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  41.  42
    AI Healthcare ChatBot_ using Machine Learning (13th edition).Brahmtej B. Bargali Akash S. Shinde, - 2024 - International Journal of Innovative Research in Science, Engineering and Technology 13 (12):20832-20837. Translated by Akash S Shinde.
    The rapid advancement of artificial intelligence (AI) and machine learning (ML) has led to significant innovations in the healthcare sector. One such development is AI-powered healthcare chatbots, which assist patients and medical professionals by providing medical guidance, symptom assessment, and appointment scheduling. This paper presents the design and implementation of an AI healthcare chatbot using machine learning techniques. The chatbot leverages natural language processing (NLP) and deep learning models to understand and respond to user queries effectively. Experimental (...)
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  42. Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 4.
    Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random Forest over a restful (...)
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  43. Semantic Error Prediction: Estimating Word Production Complexity.David Strohmaier & Paula Buttery - 2024 - Proceedings of the 13Th Workshop on Natural Language Processing for Computer Assisted Language Learning 13:209-225.
    Estimating word complexity is a well-established task in computer-assisted language learning. So far, however, complexity estimation has been largely limited to comprehension. This neglects words that are easy to comprehend, but hard to produce. We introduce semantic error prediction (SEP) as a novel task that assesses the production complexity of content words. Given the corrected version of a learner-produced text, a system has to predict which content words replace tokens from the original text. We present and analyse one example (...)
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