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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  ...  Low-level and image metadata are the most widely used features set.  ...  The supervised machine learning algorithms often used from the surveyed literature are Decision Tree, Fuzzy Logic, Support Vector Machine, Neural Networks, Bayesian Network, and Genetic Algorithm.  ... 
doi:10.14569/ijacsa.2020.0111196 fatcat:j4c4uyz2jfftfi3o6yohgyfvem

Text-rating review discrepancy (TRRD): an integrative review and implications for research

Amal Almansour, Reem Alotaibi, Hajar Alharbi
2022 Future Business Journal  
From surveying the literature, it is concluded that the quality of the rating scores used for sentiment analysis models is questionable as it might not reflect the sentiment of the associated reviews texts  ...  OCRs solution models.  ...  The authors, therefore, gratefully acknowledge DSR technical and financial support.  ... 
doi:10.1186/s43093-022-00114-y fatcat:i6oq4aloknh3doycv66mspruxu

Detection of Phishing Websites using Machine Learning

Shwetha et al., Shwetha et al.,, TJPRC
2020 International Journal of Mechanical and Production Engineering Research and Development  
There are many anti-phishing methods such as blacklist, heuristic, visual similarity and, machine learning.  ...  This paper proposes a methodology of phishing identification framework where various machine learning algorithms like random forest, support vector machine, logistic regression are used for the comparison  ...  party services with machine learning techniques to detect phish.  ... 
doi:10.24247/ijmperdjun2020644 fatcat:qe5fi2x5bzgmfhngnmhaoky67q

Evaluation of spam detection and prevention frameworks for email and image spam

Pedram Hayati, Vidyasagar Potdar
2008 Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services - iiWAS '08  
Excessive amounts of spam are not only reducing the quality of information available on the Internet but also creating concern amongst search engines and web users.  ...  This paper aims to analyse existing works in two different categories of spam domains -email spam and image spam to gain a deeper understanding of this problem.  ...  Is the technique fast enough to scale on public email servers? 4. Does the technique use supervised or unsupervised machine learning approach? 5.  ... 
doi:10.1145/1497308.1497402 dblp:conf/iiwas/HayatiP08 fatcat:j3qm2maj7bbitl36fs3kfpfxpe

Aspect-Oriented Analytics of Big Data

No'aman M. Ali
2020 International Baltic Conference on Databases and Information Systems  
Next, we plan to measure the polarity of the reviews and opinion units. Finally, we plan to visualize the results in the form of domain-oriented reports.  ...  Our proposal presents a multilayer classifier for consumers' reviews. The first layer is used to categorize reviews into the aspect and non-aspect classes.  ...  Boris Novikov, for his guidance, encouragement, and advice he has provided throughout the previous period of my doctoral studies and is still ongoing.  ... 
dblp:conf/balt/Ali20 fatcat:52fro6oqgjhqrk3grqgsyngmwi

IMPULSIVE INTERMODAL CYBER BULLYING RECOGNITION FROM PUBLIC NETS

Pradheep. T
2018 International Journal of Advanced Research in Computer Science  
Finally the cyberbully data will be classified into Physical bullying, Social bullying and Verbal bullying using classifiers.  ...  The cyberbully image will be detected using the computer vision algorithm which includes two methods like Image Similarity and Optical Character Recognition (OCR).  ...  He used a method quantitative data gathering techniques embedded with grounded theory for detecting the cyberbully content.  ... 
doi:10.26483/ijarcs.v9i3.6009 fatcat:mmzwfq65lrepbnfly4g6ri4d3a

CamForensics

Animesh Srivastava, Puneet Jain, Soteris Demetriou, Landon P. Cox, Kyu-Han Kim
2017 Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems - SenSys '17  
This paper presents results from the first large-scale study of visual privacy leaks in the wild. We build CamForensics to identify the kind of information that apps extract from camera data.  ...  An app violates visual privacy if it extracts information from camera data in unexpected ways.  ...  For this purpose, we use a very simple machine learning technique and implement it using the open-source framework, TensorFlow.  ... 
doi:10.1145/3131672.3131683 dblp:conf/sensys/SrivastavaJDCK17 fatcat:x6jivl5wxvfz5f5ldn2t7txxu4

A review on Video Classification with Methods, Findings, Performance, Challenges, Limitations and Future Work

Md Shofiqul Islam, Mst Sunjida Sultana, Uttam Kumar Roy, Jubayer Al Mahmud
2021 Jurnal Ilmiah Teknik Elektro Komputer dan Informatika  
Many machines learning approach has been developed for the classification of video to save people time and energy.  ...  Secondly, overall inconvenience, difficulties, shortcomings and potential work, data, performance measurements with the related recent relation in science, deep learning and the model of machine learning  ...  Video classification is part of mining which analyzes text through natural language processing, video by machine linguistics in order to find views of people by gathering and analyzing social and other  ... 
doi:10.26555/jiteki.v6i2.18978 fatcat:jbdixy73xvfurpmyezlk755xzu

Efficient Automated Processing of the Unstructured Documents using Artificial Intelligence: A Systematic Literature Review and Future Directions

Dipali Baviskar, Swati Ahirrao, Vidyasagar Potdar, Ketan Kotecha
2021 IEEE Access  
The purpose of this Systematic Literature Review (SLR) is to recognize, and analyze research on the techniques used for automatic information extraction from unstructured documents and to provide directions  ...  Our SLR discovered that AI-based approaches have a strong potential to extract useful information from unstructured documents automatically.  ...  Machine Learning [53] , [16] : The studied approaches were classified into three categories of the techniques, which In Supervised Machine Learning approaches, the model learns from the historical or  ... 
doi:10.1109/access.2021.3072900 fatcat:lrbzlmo5gnczhadnrxd2aoqz4u

ETDR: An Exploratory View of Text Detection and Recognition in Images and Videos

Chaitra Yuvaraj Lokkondra, Dinesh Ramegowda, Gopalakrishna Madigondanahalli Thimmaiah, Ajay Prakash Bassappa Vijaya, Manjula Hebbaka Shivananjappa
2021 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
Third, the process flow for extracting information from the text and the existing machine learning and deep learning techniques used to train the model was described.  ...  Fourth, explain assessment measures that are used to validate the model. Finally, it integrates the uses and difficulties of text extraction across a wide range of fields.  ...  The rapid use of Smartphone's and online social media has resulted in gathering an enormous volume of pictorial data, particularly the enormous and growing gatherings of videos on websites and social media  ... 
doi:10.18280/ria.350504 fatcat:l47wy45vwjdc3dobxy3xxp7rqe

Editorial Context Solution Using Real Time Interactive Visualisation–Data Driven Story Telling

A. Akshai R, B. Meenakshi S, C. Rohit Krishnan, D. S Shweta, E. Venkatesh B P
2018 International Journal of Information and Electronics Engineering  
It inculcates reformative education, saves time during the analysis of surveys and feedback analysis.  ...  Continuous learning can create new insights and perspectives in life. Efficient method of learning makes it possible to attract even non-readers.  ...  Fig. 1 . 1 Represents that understanding the things visually is easy than words. Fig. 2 . 2 The circle represents the content which is gathered from the television internet and radio.  ... 
doi:10.18178/ijiee.2018.8.3.691 fatcat:d7zotitkbfhipcjahewcnul3cq

A Review of Computer Vision Methods in Network Security [article]

Jiawei Zhao, Rahat Masood, Suranga Seneviratne
2020 arXiv   pre-print
Traditional machine learning methods have been frequently used in the context of network security.  ...  However, such methods are more based on statistical features extracted from sources such as binaries, emails, and packet flows.  ...  Authors used the open-source OCR engine Tesseract 2 that used the detected words as features in data going into a machine learning classifier. Hara et al.  ... 
arXiv:2005.03318v1 fatcat:pcng7535obec3l6fejkllbi3ii

A Comparative Review on Object Detection System for Visually Impaired

Dr K Sreenivasulu, Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
The framework first suggests the approach to take an image from the camera and the area of the target to retrieve the object from the context and derive a text pattern from that object.  ...  The observed text is linked to the blueprint and translated into the performance of the voice. Localized and binarized text patterns utilising Optical Character Recognition (OCR).  ...  learning techniques are quite new, the first machine learning projects They date from theeighties,and those of more complex techniques based on machine learning such as Deep learning are even more recent  ... 
doi:10.17762/turcomat.v12i2.1442 fatcat:26hqsbkvd5flxlgy4chejkllre

Text Analytics: the convergence of Big Data and Artificial Intelligence

Antonio Moreno, Teófilo Redondo
2016 International Journal of Interactive Multimedia and Artificial Intelligence  
Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semisupervised enhancement of systems, but they also present a number of limitations  ...  Text analytics is applicable to most industries: it can help analyze millions of emails; you can analyze customers' comments and questions in forums; you can perform sentiment analysis using text analytics  ...  machine learning techniques.  ... 
doi:10.9781/ijimai.2016.369 fatcat:v4e6utdnxrb6hpszmdhidss7g4

Context-aware Image Tweet Modelling and Recommendation

Tao Chen, Xiangnan He, Min-Yen Kan
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
To bridge this gap, we move from the images' pixels to their context and propose a context-aware image tweet modelling (CITING) framework to mine and fuse contextual text to model such social media images  ...  ., low-level SIFT or high-level detected objects, are far from adequate in interpreting the necessary semantics latent in image tweets.  ...  We also would like to thank Yongfeng Zhang and Hanwang Zhang for their help and discussions.  ... 
doi:10.1145/2964284.2964291 dblp:conf/mm/ChenHK16 fatcat:nepnjdu5vbffbhrhkisac5p5fe
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