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[1]
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A Study on Email Spam Detection and Filtering Techniques
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NULL |
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[2]
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ONLINE JOB SCAM DETECTION USING SMART SYSTEM
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2022 |
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[3]
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Multilayer Perceptron Optimization Approaches for Detecting Spam on Social Media Based on Recursive Feature Elimination
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Applications of Artificial Intelligence and Machine …,
2022 |
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[4]
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Advances in spam detection for email spam, web spam, social network spam, and review spam: ML-based and nature-inspired-based techniques
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Journal of Computer Security,
2021 |
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[5]
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An Analysis of Machine Learning Algorithms and Deep Neural Networks for Email Spam Classification using Natural Language Processing
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… and Logistics, and …,
2021 |
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[6]
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Adaptive intelligent learning approach based on visual anti-spam email model for multi-natural language
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2021 |
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[7]
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KNN-ROBKP: An Approach for Improvement of Spam Detection over Documents
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2021 |
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[8]
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Novel email spam detection method using sentiment analysis and personality recognition
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2020 |
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[9]
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Manipulation of Email Data Using Machine Learning and Data Visualization
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2020 |
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[10]
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An Anti-Spam Detection Model For Emails Of Multi-Natural Language
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2019 |
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IMPROVED ELECTRONIC MAIL CLASSIFICATION USING HYBRIDIZED ROOT WORD EXTRACTIONS
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2019 |
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AVALIA??O DO EFEITO DA VARIA??O DA UMIDADE NO COMPORTAMENTO MECANíSTICO DE UM TRECHO DA ESTRADA DE FERRO CARAJáS
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Thesis,
2019 |
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[13]
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Spam Detection in Online Social Networks Using Feed Forward Neural Network
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Conference Paper,
2018 |
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[14]
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An Intelligent Framework for Issue Ticketing System Based on Machine Learning
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2018 |
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[15]
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Email Classification Using Artificial Neural Network
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2018 |
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[16]
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Implementing an Agent-based Multi-Natural Language Anti-Spam Model
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2018 |
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Spam Filtration using Boyer Moore Algorithm and Naïve Method
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International Journal of Computer Applications,
2018 |
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[18]
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Spam detection using semantic web in mail services
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2018 |
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[19]
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Machine Learning Approach to Predict Student Academic Performance
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2018 |
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[20]
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A Comparative Analysis of Various Spam Classifications
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Progress in Intelligent Computing Techniques: Theory, Practice, and Applications,
2018 |
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[21]
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A Content-Based Phishing Email Detection Method
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2017 |
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[22]
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A Comparative Analysis of Various Spam
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2017 |
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[23]
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Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset
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Future Internet,
2017 |
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[24]
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Email Classification Using Machine Learning Algorithms
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International Journal of Engineering and Technology,
2017 |
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[25]
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A New Machine Learning based Approach for Text Spam Filtering Technique
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2017 |
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[26]
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An Optimized Approach to Improve the Quality of Education
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2017 |
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[27]
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Machine Learning Approach to Predict and Improve Student Academic Performance
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2017 |
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[28]
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New approaches for content-based analysis towards Online Social Network spam detection
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2016 |
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[29]
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PROCEDIMENTO PARA PLANEJAMENTODO EMPREGO DAS FOR?AS ARMADAS BRASILEIRAS EM APOIO A LOGíSTICA HUMANITáRIA NAGEST?O DE DESASTRES
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Thesis,
2016 |
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[30]
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Technical Study of Spam Filtering Process
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2016 |
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[31]
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A New SMS Spam Detection Method Using Both Content-Based and Non Content-Based Features
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Advanced Computer and Communication Engineering Technology,
2016 |
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[32]
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CONTENT FILTERING USING ARITIFICIAL INTELLIGENCE
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International Journal of Advanced Research in Computer Engineering & Technology,
2016 |
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Does sentiment analysis help in bayesian spam filtering?
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Hybrid Artificial Intelligent Systems,
2016 |
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E-Mail Spam Detection Using SVM and RBF
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2016 |
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[35]
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A Survey Paper on Spam Mail Detection Using RFD
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2016 |
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[36]
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Spam Mail Detection Using Relevance Feature Discovery
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International Journal of Science and Research (IJSR) ,
2016 |
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[37]
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Incremental learning for large-scale stream data and its application to cybersecurity
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2015 |
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[38]
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Spam Detection Techniques: A Review
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International Journal of Science and Research,
2015 |
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[39]
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An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing
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Journal of Intelligent Learning Systems and Applications,
2015 |
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[40]
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Review on Effective Email Classification for Spam and Non Spam Detection on Various Machine Learning Techniques
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International Journal on Recent and Innovation Trends in Computing and Communication,
2015 |
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[41]
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SPAM-NSGA-II-NVBYS: AN EFFICIENT HYBRID APPROACH FOR E-MAIL SPAM FILTERING
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ARPN Journal of Engineering and Applied Sciences,
2015 |
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The challenges faced by management science research scholars in different stages of research: A Study for Maharashtra (INDIA)
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International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS),
2015 |
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[43]
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UMA PROPOSTA PARA SISTEMA DE GERÊNCIA DE PAVIMENTOSAPLICADA A AEROPORTOS MILITARES
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2015 |
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[44]
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Penanganan Fitur Kontinyu dengan Feature Discretization Berbasis Expectation Maximization Clustering untuk Klasifikasi Spam Email Menggunakan Algoritma ID3
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Journal of Intelligent Systems,
2015 |
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[45]
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A Case Study of User-Level Spam Filtering.
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2014 |
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[46]
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Shrihari Ahire Vishakha Panjabi Rahul Jagtap Department of Computer Engineering Department of Computer Engineering Department of Computer Engineering
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International Journal of Scientific & Engineering Research,
2014 |
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[47]
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Inured to Obscenity but Sensitive to Pornography: Aren’t Our Definitions Blurred?
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International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS),
2014 |
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[48]
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SECUMAIL [Secure Email System]
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International Journal of Scientific & Engineering Research,
2014 |
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[49]
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A Case Study of User-Level Spam Filtering
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K Bajaj, J Pieprzyk - crpit.com,
2014 |
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Identifying spam e-mail messages using an intelligence algorithm
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Decision Science Letters,
2014 |
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[51]
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Effective Spam Detection Method for Email
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IOSR Journal of Computer Science (IOSR-JCE),
2014 |
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[52]
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A Review on Different Spam Detection Approaches
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International Journal of Engineering Trends and Technology (IJETT),
2014 |
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[53]
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Spam Filtering using K mean Clustering with Local Feature Selection Classifier
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International Journal of Computer Applications,
2014 |
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[54]
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SURVEY PAPER ON INTELLIGENT SYSTEM FOR TEXT AND IMAGE SPAM FILTERING
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2013 |
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[55]
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Can We CAN the Email Spam
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Cybercrime and Trustworthy Computing Workshop (CTC), 2013 Fourth. IEEE,
2013 |
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[56]
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A Behavioral Spam Detection System
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Future Computer, Communication, Control and Automation. Springer Berlin Heidelberg,,
2012 |
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[57]
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Baeza-Yates and Navarro approximate string matching for spam filtering
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Innovative Computing Technology (INTECH), 2012 Second International Conference on. IEEE,
2012 |
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[58]
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An Off - Line Character Recognition System for Marathi Handwritten S cript, a Review and Study
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International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS),
2012 |
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[59]
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UMA METODOLOGIA PARA APOIO AO DESENVOLVIMENTO SEMI-AUTOMATICO DE SISTEMAS ´ MULTI-AGENTES
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2012 |
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[60]
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MINISTÉRIO DA DEFESAEXÉRCITO BRASILEIRODEPARTAMENTO DE CIÊNCIA E TECNOLOGIAINSTITUTO MILITAR DE ENGENHARIACURSO DE MESTRADO EM ENGENHARIA MECÂNICA
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2012 |
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[61]
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Approximate String Matching for Spam Filtering
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2012 |
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[62]
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AN EVALUATION OF TIME COMPLEXITIES OF BAYESIAN BASED AND HYBRIDIZED WORD STEMMING TECHNIQUE FOR FILTERING ADVANCED FEE …
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