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Multi-field learning for email spam filtering

Wuying Liu, Ting Wang
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
Through the investigation of email document structure, this paper proposes a multi-field learning (MFL) framework, which breaks the multi-field document Text Classification (TC) problem into several sub-document  ...  is spam.  ...  Further research will concern semi-supervised learning, active learning, and personal learning for spam filtering within MFL framework.  ... 
doi:10.1145/1835449.1835595 dblp:conf/sigir/LiuW10 fatcat:dflmhusxmra77a5fmxf4x3mtva

Online active multi-field learning for efficient email spam filtering

Wuying Liu, Ting Wang
2011 Knowledge and Information Systems  
The proposed active multi-field learning approach is based on: 1) It is cost-sensitive to obtain a label for a realworld spam filter, which suggests an active learning idea; and 2) Different messages often  ...  have a similar multi-field text structure, which suggests a multi-field learning idea.  ...  The experimental results from email and SMS spam filtering show strong support for the use of active multi-field learning in ubiquitous spam filtering.  ... 
doi:10.1007/s10115-011-0461-x fatcat:nalpyxkunvarxlwlj4ozgn2u2u

Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

Wuying Liu, Ting Wang
2012 International Journal of Computational Intelligence Systems  
index for labeled emails storing.  ...  Large-scale spam emails cause a serious waste of time and resources.  ...  Acknowledgements The authors thank the anonymous reviewers for helping to greatly improve the paper. This research is supported by the National Natural Science Foundation of China  ... 
doi:10.1080/18756891.2012.696915 fatcat:cfuwvpqlxvawbj7jm3qtpkwomy

Prediction of Spam Email using Machine Learning Classification Algorithm

P Sai Teja
2021 International Journal for Research in Applied Science and Engineering Technology  
In recent times, it is very difficult to filter spam emails as these emails are produced or created or written in a very special manner so that anti-spam filters cannot detect such emails.  ...  Unsolicited e-mail also known as Spam has become a huge concern for each e-mail user.  ...  to acknowledge the support of the Chairman, Director, Head of the Department, Department of Computer Science and Engineering, and project guides of CMR Technical Campus, Medchal, Hyderabad, Telangana, for  ... 
doi:10.22214/ijraset.2021.35226 fatcat:iw23mmwi7nhudkqs7cityfhl5q

A Review on Different Spam Detection Approaches
English

Rek ha
2014 International Journal of Engineering Trends and Technoloy  
In this paper we discuss some approaches for spam detection.  ...  Email is one of the crucial aspects of web data communication. The increasing use of email has led to a lucrative business opportunity called spamming.  ...  [2] .Ann Nosseir , Khaled Nagati and Islam Taj-Eddin performed a work," Intelligent Word-Based Spam Filter Detection Using Multi-Neural Networks".  ... 
doi:10.14445/22315381/ijett-v11p260 fatcat:htwdqek5cneqha7e3n6i7mf4pa

IMPROVED SPAMBASE DATASET PREDICTION USING SVM RBF KERNEL WITH ADAPTIVE BOOST

Sneha Singh .
2015 International Journal of Research in Engineering and Technology  
General Terms: Email Spam classification.  ...  Many spam detection techniques based on machine learning algorithms have been proposed.  ...  Although we have got good filtering techniques but still there is requirement of some better filtering techniques. So spam email filtering is major area to focus in the present field of research.  ... 
doi:10.15623/ijret.2015.0406064 fatcat:yke7lyy3arbsloytxdpqlscgru

A Survey on Various Machine Learning and Deep Learning Algorithms used for Classification of Spam and Non-Spam Emails

Shahbaz Ahmad Khanday
2019 International Journal for Research in Applied Science and Engineering Technology  
This survey gives an overview about different machine learning and deep learning algorithms to classify the spam and non-spam emails by accessing the received emails of an email client.  ...  The machine learning approaches and mechanisms like support vector machine, naive Bayesian classifier, artificial neural networks and logistic regression can be of important help to determine spam emails  ...  Literature survey explores many machine learning and deep learning algorithms can be utilized for detection and the classification of spam and non-spam emails.  ... 
doi:10.22214/ijraset.2019.4568 fatcat:inz65ryh7jbz7mjdj3n7eq6xnu

A Spam Filtering Method Based on Multi-Modal Fusion

Hong Yang, Qihe Liu, Shijie Zhou, Yang Luo
2019 Applied Sciences  
In recent years, the single-modal spam filtering systems have had a high detection rate for image spamming or text spamming.  ...  To avoid detection based on the single-modal spam filtering systems, spammers inject junk information into the multi-modality part of an email and combine them to reduce the recognition rate of the single-modal  ...  Acknowledgments: We thank William Cohen for providing the Enron dataset, and we would also like to thank Mark Dredze for providing the image dataset.  ... 
doi:10.3390/app9061152 fatcat:bbx4dwljkzdenjhjmw4ojutcd4

Machine learning for email spam filtering: review, approaches and open research problems

Emmanuel Gbenga Dada, Joseph Stephen Bassi, Haruna Chiroma, Shafi'i Muhammad Abdulhamid, Adebayo Olusola Adetunmbi, Opeyemi Emmanuel Ajibuwa
2019 Heliyon  
The upsurge in the volume of unwanted emails called spam has created an intense need for the development of more dependable and robust antispam filters.  ...  Machine learning methods of recent are being used to successfully detect and filter spam emails.  ...  Alkaht and Al Khatib [102] Randomly collected emails Multi-stage Neural Networks for filtering spam NN, MLP and Perceptron Accuracy.  ... 
doi:10.1016/j.heliyon.2019.e01802 pmid:31211254 pmcid:PMC6562150 fatcat:n7qiq4tgnzh7xi6j5c2ah335hy

An Anti-Spam Detection Model for Emails of Multi-Natural Language

Mazin Abed Mohammed, Salama A. Mostafa, Omar Ibrahim Obaid, Subhi R. M. Zeebaree, Ghani Ghani, Aida Mustapha, Mohd Farhan Md Fudzee, Mohammed Ahmed Jubair, Mustafa Hamid Hassan, Azizan Ismail, Dheyaa Ahmed Ibrahim, Fahad Taha AL-Dhief
2019 Journal of Southwest Jiaotong University  
Consequently, the literature affords various anti-spam methods that blocks or filters spam emails.  ...  The spam is one of the illegal and negative practices that involves the use of email services to send unsolicited emails such as phishing for the purpose of scamming which influences the reliability of  ...  [3] Anti-spam classification is one of the fields that machine learning is successfully handled.  ... 
doi:10.35741/issn.0258-2724.54.3.6 fatcat:b7acwfeb6zeardd6ginfbvxi5u

Spam Filtering based on Knowledge Transfer Learning

Xing Wang, Bin-Xing Fang, Hui He, Hong-Li Zhang
2015 International Journal of Security and Its Applications  
In this paper, we propose the adaptive spam filtering method for the above shortcomings.  ...  We use the transfer learning model to build the spam filtering system.  ...  This requirement has motivated the fields of SRL (statistical relational learning) and multi-relational data mining in which MLN is the most powerful theory we are focusing on.  ... 
doi:10.14257/ijsia.2015.9.10.31 fatcat:woxtawexdfddnpo5necjptsbdq

Spam Filtration using Boyer Moore Algorithm and Naïve Method

Aastha Baranwal, Gunjan Gaur, Akanksha Bhasker, Rishabh Jain
2018 International Journal of Computer Applications  
Emails are primarily being used for transporting information in a quicker and well-organized way.  ...  There are numerous approaches that have been formulated to screen the emails and organize them as spam and non-spam.  ...  Rishabh Jain for his motivation and valuable advice. We are also immensely grateful to our HOD and coordinators for their support. Although errors present in this paper, if any, are our own and  ... 
doi:10.5120/ijca2018917119 fatcat:e5kvwxcpqrfifbwldppssuzzne

Spam Classification Using MOEA/D

Rand Ahmad Atta, Soukaena H. Hashem, Ekhlas Khalaf Gbashi
2018 Al-Nahrain Journal of Science  
This paper aims to enhance the e-mail spam filtering by using multiobjective evolutionary algorithm for classifying the e-mail messages to spam or non-spam in high accuracy.  ...  So the multi objective optimization algorithm has the ability to deal with a many objectives instead of one objective, because of the difficulties in the classical methods of multi objectives optimization  ...  equal 3 for the classifier email spam filtering.  ... 
doi:10.22401/anjs.21.4.14 fatcat:e45wbndlibb77p623y5b4sx3da

E-Mail Spam Detection Using Refined MLP with Feature Selection

Harjot Kaur, Er. Prince Verma
2017 International Journal of Modern Education and Computer Science  
This serious issue has generated a need for efficient and effective anti-spam filters that filter the email into spam or ham email.  ...  Various spam filters are labelled into two categories learning and non-machine learning techniques.  ...  ACKNOWLEDGMENT The author expresses its humble thanks to CT group of Engineering, Management, and Technology for their motivational participation and encouragement in the research field.  ... 
doi:10.5815/ijmecs.2017.09.05 fatcat:gxxzb7bv55g3tjxgxjz4mmn7be

Different Techniques for Spam Filtering: A Survey

Vandana S. Ahire
2017 International Journal of Innovative and Emerging Research in Engineering  
In this paper the overview of existing e-mail spam filtering methods like keyword based, Machine learning, Neural networks is given.  ...  Spam is currently of grave and escalating concern and it is challenging to develop spam filters. There are many different techniques to develop a correct and user friendly spam filter.  ...  We use ( ) and ( ) to denote the probability that an email is a spam email and a legitimate email, respectively. The filter parses each email for spam keywords.  ... 
doi:10.26769/ijiere.2017.4.10.191503 fatcat:kbgyicxxqjha3oenjbgyrhfci4
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