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On the Effects of Spam Filtering and Incremental Learning for Web-Supervised Visual Concept Classification

Matthias Springstein, Ralph Ewerth
2016 Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval - ICMR '16  
In this paper, we investigate several aspects of a web-supervised system that has to be adapted to another target domain: 1.) the effect of incremental learning, 2.) the effect of spam filtering, and 3  ...  Deep neural networks have been successfully applied to the task of visual concept classification. However, they require a large number of training examples for learning.  ...  CONCLUSIONS In this paper, we have investigated the effect of spam filtering and incremental learning for a web-supervised deep learning framework for visual concept classification.  ... 
doi:10.1145/2911996.2912072 dblp:conf/mir/SpringsteinE16 fatcat:a5qcsdx23bev5h3k65ufqqgfva

Artificial immune system inspired behavior-based anti-spam filter

Xun Yue, Ajith Abraham, Zhong-Xian Chi, Yan-You Hao, Hongwei Mo
2006 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Two main concepts are introduced, which defines the behavior-based characteristics of spam and to continuously identify the similar groups of spam when processing the spam streams.  ...  This paper proposes a novel behavior-based anti-spam technology for email service based on an artificial immune-inspired clustering algorithm.  ...  Authors would like to thanks the three anonymous referees for the constructive comments that helped to enhance the quality and presentation of this paper.  ... 
doi:10.1007/s00500-006-0116-0 fatcat:lxgft4o7cbelfkcelbjvud7sym

Phishing Image Spam Classification Research Trends: Survey and Open Issues

Ovye John Abari, Nor Fazlida, Fatimah Khalid, Mohd Yunus, Noor Afiza
2020 International Journal of Advanced Computer Science and Applications  
The methods of image spam classification as identified in this study are supervised machine learning, unsupervised machine learning, semi-supervised machine learning, content-based and statistical learning  ...  This study reviews articles on phishing image spam classification published from 2006 to 2020 based on spam classification application domains, datasets, features sets, spam classification methods, and  ...  ACKNOWLEDGMENT The authors would like to acknowledge the Universiti Putra Malaysia for supporting this research.  ... 
doi:10.14569/ijacsa.2020.0111196 fatcat:j4c4uyz2jfftfi3o6yohgyfvem

Machine Learning Framework to Analyze Against Spear Phishing

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In this paper we discussed different algorithms and machine learning concepts that can be implemented on the datasets, we taken email spam filter dataset for experiment and analysis, as the Advanced persistent  ...  This paper will measure different machine learning algorithms performance on spam email filtering on the huge datasets.  ...  The classification is a predictive modelling, the classification is one of the major task of the supervised learning, where responsibility of the classification model is to assign class label to the target  ... 
doi:10.35940/ijitee.l3802.1081219 fatcat:v65cevq4ebhlxja5dfdx2tnysu

A Comprehensive Survey for Intelligent Spam Email Detection

Asif Karim, Sami Azam, Bharanidharan Shanmugam, Krishnan Kannoorpatti, Mamoun Alazab
2019 IEEE Access  
The tremendously growing problem of phishing e-mail, also known as spam including spear phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e-mail filters.  ...  Based on the number the relevance of an emerging intelligent method, papers representing each method were identified, read, and summarized.  ...  The section after that (Section IV) is based on several Bio-inspired and Machine Learning based approaches for spam classification and detection.  ... 
doi:10.1109/access.2019.2954791 fatcat:ikt6cayggbb2dkrm52fxzz2dqm

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  
Our review covers survey of the important concepts, attempts, efficiency, and the research trend in spam filtering.  ...  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.  ...  They surveyed the important concepts, efforts, effectiveness, and the trend in spam filtering.  ... 
doi:10.1016/j.heliyon.2019.e01802 pmid:31211254 pmcid:PMC6562150 fatcat:n7qiq4tgnzh7xi6j5c2ah335hy

A review of machine learning approaches to Spam filtering

Thiago S. Guzella, Walmir M. Caminhas
2009 Expert systems with applications  
In this paper, we present a comprehensive review of recent developments in the application of machine learning algorithms to Spam filtering, focusing on both textual-and image-based approaches.  ...  Instead of considering Spam filtering as a standard classification problem, we highlight the importance of considering specific characteristics of the problem, especially concept drift, in designing new  ...  Acknowledgements This work was supported by grants from UOL, through its Bolsa Pesquisa program (process number 20060519110414a), FAPEMIG and CNPq.  ... 
doi:10.1016/j.eswa.2009.02.037 fatcat:gf5z34w6arcdzh2w36tgefqppa

Bringing Shape to Textual Data – A Feasible Demonstration

Anoud Shaikh, Naeem Ahmed Mahoto, Mukhtiar Ali Unar
2019 Mehran University Research Journal of Engineering and Technology  
A prototype has been developed to demonstrate the effectiveness and potential worth of proposed approach to display how unstructured data (i.e. news articles in this study) has been brought to a shape  ...  The results reveal the fact that how events, celebrities and popular news-items have been covered in the electronic media, and it also represents subjectivity of topical news events.  ...  ACKNOWLEDGMENTS The authors wish to thank continued support of the  ... 
doi:10.22581/muet1982.1904.04 fatcat:yackjesnjvbmlgohnpcyofypiu

An Overview of Concept Drift Applications [chapter]

Indrė Žliobaitė, Mykola Pechenizkiy, João Gama
2015 Studies in Big Data  
This chapter provides an application oriented view towards concept drift research, with a focus on supervised learning tasks.  ...  First we overview and categorize application tasks for which the problem of concept drift is particularly relevant.  ...  This work was partially supported by European Commission through the project MAESTRA (Grant number ICT-2013-612944).  ... 
doi:10.1007/978-3-319-26989-4_4 fatcat:nckbz7bk4natlpnkx37co4dznu

Learning Concept Drift Using Adaptive Training Set Formation Strategy

Nabil M. Hewahi, Sarah N. Kohail
2013 International Journal of Technology Diffusion  
In data mining the phenomenon of change in data distribution over time is known as concept drift. In this research, we propose an adaptive supervised learning with delayed labeling methodology.  ...  Results indicate the effectiveness of the proposed method over other methods in terms of classification accuracy.  ...  In this thesis we consider the problem of concept drift in supervised learning where the true classification for each instance (label) is delayed.  ... 
doi:10.4018/jtd.2013010103 fatcat:sa3u63uu2jge5m3mpwkh5f6pcm

Predicting Rogue Content and Arabic Spammers on Twitter

Adel R. Alharbi, Amer Aljaedi
2019 Future Internet  
Twitter is one of the most popular online social networks for spreading propaganda and words in the Arab region.  ...  In our previous study, we estimated that rogue and spam content accounted for approximately three quarters of all content with Arabic trending hashtags in Saudi Arabia.  ...  Supervised Classification Random forest is a supervised learning algorithm that can be used for classification as well as regression.  ... 
doi:10.3390/fi11110229 fatcat:pvhlcsssbjfohhlgmlzyrkhkvq

One-pass-throw-away learning for cybersecurity in streaming non-stationary environments by dynamic stratum network

Mongkhon Thakong, Suphakant Phimoltares, Saichon Jaiyen, Chidchanok Lursinsap, Hua Wang
2018 PLoS ONE  
The adaptive solution of learning has been widely designed in several security applications. For example, supervised learning techniques of classification are used for spam filtering [10, 15, 16] .  ...  Hybrid approaches combining supervised and unsupervised techniques based on machine learning algorithms were also used for the detection of network attacks [23].  ...  Acknowledgments This work is supported by the Thailand Research Fund (TRF) under grant number RTA6080013. One-pass-throw-away learning by dynamic stratum network  ... 
doi:10.1371/journal.pone.0202937 pmid:30188908 pmcid:PMC6126810 fatcat:ygy4osz5czesxljxd6zkksdtqi

A Survey on Sentimental Analysis Approaches using Machine Learning Algorithms

Anith Ashok, Dr. Sandeep Monga
2022 International Journal for Research in Applied Science and Engineering Technology  
It is one of the prominent fields of data mining that deals with the identification and analysis of sentimental contents generally available at social media.  ...  In this work, a survey has been conducted on various work done in the past on sentiment analysis which includes opinion mining methods, machine learning based approaches and hybrid approaches which combines  ...  Next the instance-based approach for filtering the spams allows the sharing of instances with the effort of labeling e-mail as spam.  ... 
doi:10.22214/ijraset.2022.42005 fatcat:ss2f2lpznzcktakldpbete3evu

Blogosphere

Nitin Agarwal, Huan Liu
2008 SIGKDD Explorations  
Yu , and Alan Zheng Zhao for collaboration, discussion, and valuable comments. • This work is, in part, sponsored by AFOSR and ONR grants in 2008.  ...  approaches • Some critical differences between web spam detection and splog detection -The content on blog sites is very dynamic as compared to that of web pages, so content based spam filters are ineffective  ...  of the blog posts/blog sites • tf-idf could be used for indexing the blog entries • Folksonomies could be considered as class labels • Supervised machine learning could be performed and learned models  ... 
doi:10.1145/1412734.1412737 fatcat:v4ec3j66aragrnczjlisl6yowe

A Mapping Study to Investigate Spam Detection on Social Networks

Balogun Abiodun Kamoru, Azmi Jaafar, Masrah Azrifah Azmi Murad
2017 International Journal of Applied Information Systems  
Existing research on filtering techniques such as collaborative filters and behavioral analysis filters are able to significantly reduce spam.  ...  Social networks such as Facebook, Twitter and SinaWeibo have become increasingly important for reaching millions of user globally.  ...  This work will not be possible without the help of Associate Professor Dr.Azmi Jaafar and Associate Professor Dr Masrah Azrifah Azmi Murad for her support during the cause of writing the paper.  ... 
doi:10.5120/ijais2017451652 fatcat:c47pbz4labcrhi3e5amf6hlj3u
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