Documents T210C0+T370C0_['tfidf', 'emails', 'document', 'spam']_docs.csv

csv
YearTitleScore
2004 On enhancing the performance of spam mail filtering system using semantic enrichment 0.49
2005 Spam Filtering based on Preference Ranking 0.53
2005 An Email Classification Model Based On Rough Set Theory 0.49
2006 Application and evaluation of bayesian filter for chinese spam 0.50
2006 Content based SMS spam filtering 0.49
2006 Towards an Ontology Driven Spam Filter 0.49
2007 On Extendable Software Architecture for Spam Email Filtering 0.50
2008 A Novel Method for Image Spam Filtering 0.52
2008 The Impact of Noise in Spam Filtering: A Case Study 0.48
2009 Looking into the past to better classify web spam 0.56
2009 Language-model-based detection cascade for efficient classification of image-based spam e-mail 0.50
2010 An Approach to Image Spam Filtering Based on Base64 Encoding and N-Gram Feature Extraction 0.53
2010 An Empirical Study of Spam: Analyzing Spam Sending Systems and Malicious Web Servers 0.51
2010 An In-Depth Analysis Of Spam And Spammers 0.48
2010 Using Feature Selection to Speed Up Online SVM Based Spam Filtering 0.48
2011 A Spam Filtering Method Based on Multi-modal Features Fusion 0.52
2011 Reducing Classification Times for Email Spam Using Incremental Multiple Instance Classifiers. 0.50
2012 A paragraph-inserted word salad filtering algorithm 0.49
2013 Domain Registration Date Retrieval System of URLs in E-Mail Messages for Improving Spam Discrimination 0.50
2013 Collaborative spam filtering based on incremental ontology learning 0.49
2013 Spam e-mail classification based on the IFWB algorithm 0.48
2014 Efficient spam filtering based on informative features extracted from the header fields and the URLs in the message. 0.51
2015 Web Service-Enabled Spam Filtering with Naïve Bayes Classification 0.52
2015 Image Spam Classification Using Neural Network. 0.49
2015 Clustering spam emails into campaigns 0.48
2020 Malicious Text Identification: Deep Learning From Public Comments And Emails 0.52
2020 DeepCapture: Image Spam Detection Using Deep Learning and Data Augmentation 0.49
2021 Enhancing Multimodal Clustering Framework with Deep Learning to Reveal Image Spam Authorship 0.49
2021 Adaptive intelligent learning approach based on visual anti-spam email model for multi-natural language 0.48
2022 Machine Learning Techniques for Spam Detection in Email and IoT Platforms: Analysis and Research Challenges 0.48