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Miscellaneous Contributed Journals and Academic Newsletters
by Nur’Ain Maulat Samsudin, Cik Feresa binti Mohd Foozy, Nabilah Alias, Palaniappan Shamala, Nur Fadzilah Othman, Wan Isni Sofiah Wan Din
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YouTube has become a popular social media among the users. Due to YouTube popularity, it became a platform for spammer to distribute spam through the comments on YouTube. This has become a concern because spam can lead to phishing attack which the target can be any user that click any malicious link. Spam has its own features that can be analyzed and detected by classification. Hence, enhancement features are proposed to detect YouTube spam. In order to conduct the experiments, a YouTube Spam...
Topics: Classification, Detection, Machine learning, Spam
Miscellaneous Contributed Journals and Academic Newsletters
by Raswitha Bandi, J Amudhavel, R Karthik
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A reasonable distributed memory-based Computing system for machine learning is Apache Spark. Spark is being superior in computing when compared with Hadoop. Apache Spark is a quick, simple to use for handling big data that has worked in modules of Machine Learning, streaming SQL, and graph processing. We can apply machine learning algorithms to big data easily, which makes it simple by using Spark and its machine learning library MLlib, even this can be made simpler by using the Python API...
Topics: Apache spark, Machine Learning, PySpark, SCALA
Miscellaneous Contributed Journals and Academic Newsletters
by Nabilah Alias, Cik Feresa Mohd Foozy, Sofia Najwa Ramli
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Nowadays, social media (e.g., YouTube and Facebook) provides connection and interaction between people by posting comments or videos. In fact, comments are a part of contents in a website that can attract spammer to spreading phishing, malware or advertising. Due to existing malicious users that can spread malware or phishing in the comments, this work proposes a technique used for video sharing spam comments feature detection. The first phase of the methodology used in this work is dataset...
Topics: Video spam comment, Machine learning, Feature selection
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Sholihah Zaini, Deris Stiawan, Mohd Faizal Ab Razak, Ahmad Firdaus, Wan Isni Sofiah Wan Din, Shahreen Kasim, Tole Sutikno
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The increasing development of the Internet, more and more applications are put into websites can be directly accessed through the network. This development has attracted an attacker with phishing websites to compromise computer systems. Several solutions have been proposed to detect a phishing attack. However, there still room for improvement to tackle this phishing threat. This paper aims to investigate and evaluate the effectiveness of machine learning approach in the classification of...
Topics: Intrusion detection, Machine learning, Malware, Phishing, Website
Miscellaneous Contributed Journals and Academic Newsletters
by Ong Vienna Lee, Ahmad Heryanto, Mohd Faizal Ab Razak, Anis Farihan Mat Raffei, Danakorn Nincarean Eh Phon, Shahreen Kasim, Tole Sutikno
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The openness of the World Wide Web (Web) has become more exposed to cyber-attacks. An attacker performs the cyber-attacks on Web using malware Uniform Resource Locators (URLs) since it widely used by internet users. Therefore, a significant approach is required to detect malicious URLs and identify their nature attack. This study aims to assess the efficiency of the machine learning approach to detect and identify malicious URLs. In this study, we applied features optimization approaches by...
Topics: Android, Detection system, Features optimization, Machine learning, URLs
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Syuhada Selamat, Fakariah Hani Mohd Ali
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Currently, the volume of malware grows faster each year and poses a thoughtful global security threat. The number of malware developed increases as computers became interconnected, at an alarming rate in the 1990s. This scenario resulted the increment of malware. It also caused many protections are built to fight the malware. Unfortunately, the current technology is no longer effective to handle more advanced malware. Malware authors have created them to become more difficult to be evaded from...
Topics: Dynamic analysis, Hybrid analysis, Machine learning, Malware, Static analysis
Miscellaneous Contributed Journals and Academic Newsletters
by A. Adeleke, N. Samsudin, A. Mustapha, S. Ahmad Khalid
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Classification of Quranic verses into predefined categories is an essential task in Quranic studies. However, in recent times, with the advancement in information technology and machine learning, several classification algorithms have been developed for the purpose of text classification tasks. Automated text classification (ATC) is a well-known technique in machine learning. It is the task of developing models that could be trained to automatically assign to each text instances a known label...
Topics: Classifiers, Feature selection, Holy Quran, Machine learning, Text classification
Transportation has been considered as the backbone of the economy for the past many years. Unfortunately, since few years due to the uncontrolled urbanization and inadequate planning, countries are facing problem of congestion. The congestion is hindering the economic growth and also causing environmental issues. This has caused serious concerns among the major economies of the world, especially in Asia-Pacific region. Many countries are playing an active role in eradicating this problem and...
Topics: Big data analytics, Machine learning, Transport framework, Uncontrolled urbanization
Miscellaneous Contributed Journals and Academic Newsletters
by Haider O. Lawend, Anuar M. Muad, Aini Hussain
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This paper presents a proposed supervised classification technique namely flexible partial histogram Bayes (fPHBayes) learning algorithm. The traditional classification algorithms like neural network, support vector machine, first nearest neighbor, nearest subclass classifier and Gaussian mixture model classifier are accurate but slow when dealing with large number of instances. In additional to that these algorithms might require to be retrain when the classes changes. On the other hand,...
Topics: Classification, Histogram probability, Distribution, Machine learning, Naïve bayes, PHBayes
Miscellaneous Contributed Journals and Academic Newsletters
by Haseeb Ali, Mohd Najib Mohd Salleh, Rohmat Saedudin, Kashif Hussain, Muhammad Faheem Mushtaq
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The imbalanced data problems in data mining are common nowadays, which occur due to skewed nature of data. These problems impact the classification process negatively in machine learning process. In such problems, classes have different ratios of specimens in which a large number of specimens belong to one class and the other class has fewer specimens that is usually an essential class, but unfortunately misclassified by many classifiers. So far, significant research is performed to address the...
Topics: Classification, Imbalanced data, Machine learning, Majority class, Minority class
Miscellaneous Contributed Journals and Academic Newsletters
by Md. Armanur Rahman, Abid Hossen, J. Hossen, Venkataseshaiah C, Thangavel Bhuvaneswari, Aziza Sultana
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Apache Spark is an open source distributed platform which uses the concept of distributed memory for processing big data. Spark has more than 180 predominant configuration parameter. Configuration settings directly control the efficiency of Apache spark while processing big data, to get the best outcome yet a challenging task as it has many configuration parameters. Currently, these predominant parameters are tuned manually by trial and error. To overcome this manual tuning problem in this...
Topics: Apache spark, Big data, Machine learning, Self-tuning, Spark parameter
Miscellaneous Contributed Journals and Academic Newsletters
by Siti Aisyah Mohamed, Muhaini Othman, Mohd Hafizul Afifi
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The evolution of Artificial Neural Network recently gives researchers an interest to explore deep learning evolved by Spiking Neural Network clustering methods. Spiking Neural Network (SNN) models captured neuronal behaviour more precisely than a traditional neural network as it contains the theory of time into their functioning model [1]. The aim of this paper is to reviewed studies that are related to clustering problems employing Spiking Neural Networks models. Even though there are many...
Topics: Clustering, Deep learning, Machine learning, Spiking neural network, Temporal data
Miscellaneous Contributed Journals and Academic Newsletters
by Sarifah Putri Raflesia, Dinda Lestarini, Desty Rodiah, Firdaus
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Light rail transit (LRT), or fast tram is urban public transport using rolling stock similar to a tramway, but operating at a higher capacity, and often on an exclusive right-of-way. Indonesia as one of developing countries has been developed the LRT in two cities of Indonesia, Palembang and Jakarta. There are opinions toward the development of LRT, negative and positive opinions. To reveal the level of LRT development acceptance, this research uses machine learning approach to analyze the data...
Topics: Opinion mining, Machine Learning, Social Media, Naive Bayes Classifier
Miscellaneous Contributed Journals and Academic Newsletters
by Mouneshachari, Sanjay Pande M
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Human being as a parameter for assessment is a complex component for any researcher, since the field of medical sciences opens up too many unsolved queries. In this context if emotions are to be quantified it involves both scientific and certain Non-scientific issues. In terms of medical concept Electroencephalogram (EEG) helps in understanding specific regions of the brain. Since functional capabilities of regions of the brain can be understood by the probes attached to that particular region...
Topics: Classsification, EEG analysis, Human intelligence index, K nearest neighbour, Machine learning
Miscellaneous Contributed Journals and Academic Newsletters
by Nursyahirah Tarmizi, Suhaila Saee, Dayang Hanani Abang Ibrahim
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This paper presents the task of Author Identification for KadazanDusun language by using tweets as the source of data to perform Author Identification task of short text on KadazanDusun, which is considered as one the under-resourced language in Malaysia. The aim of this paper is to demonstrate Author Identification of short text on KadazanDusun. Besides, this paper also examines the performance of two machine learning algorithms on the KadazanDusun data set by analyzing the stylometric...
Topics: Author identification, Kadazan dusun, Machine learning, Stylometry, Under-resourced language
A challenging task for the modern research is to accurately diagnose the diseases prior to their treatment. Particularly in rural areas, the instant diagnosis for a life style disease is rarely available; it becomes necessary to use modern computing techniques to design intelligent prediction systems. A machine learning model is used for solving complex and non-separable prediction problems in different fields like medical diagnosis, decision support systems, biochemical analysis, image...
Topics: Intelligent systems, Machine learning, Multi-layer perceptron, Pattern classifier, Thyroid disease
Miscellaneous Contributed Journals and Academic Newsletters
by Nor Azizah Hitam, Amelia Ritahani Ismail
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Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. This paper presents a comparative performance of Machine Learning algorithms for cryptocurrency forecasting. Specifically, this paper concentrates on forecasting of time series data. SVM has several...
Topics: Artificial Intelligence, Machine Learning, Support Vector Machines, Neural Networks, Deep Learning
Miscellaneous Contributed Journals and Academic Newsletters
by Jesmeen M. Z. H., J. Hossen, S. Sayeed, C. K. Ho, Tawsif K., Armanur Rahman, E. M. H. Arif
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Recently Big Data has become one of the important new factors in the business field. This needs to have strategies to manage large volumes of structured, unstructured and semi-structured data. It’s challenging to analyze such large scale of data to extract data meaning and handling uncertain outcomes. Almost all big data sets are dirty, i.e. the set may contain inaccuracies, missing data, miscoding and other issues that influence the strength of big data analytics. One of the biggest...
Topics: Big data, Big data analytics, Data cleaning, Dirty data, Machine learning
Miscellaneous Contributed Journals and Academic Newsletters
by S. V. Shri Bharathi, Angelina Geetha
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Nowadays, identifying news biases in the social media is one of the most fundamental problems. News bias is a complex process that comprises several dimensions to be taken into account and it is interlinked with social, political and economic problems. In general, news bias has the ability to reflect opinion of people about a topic or government policies and actions. The proposed algorithm develops a system which can detect the biasedness of news topics from different news Websites. This...
Topics: Data and text mining, Machine learning, News bias, News values, Sentiment analysis
Miscellaneous Contributed Journals and Academic Newsletters
by Md. Iftakher Alam Eyamin, Md. Tarek Habib, Muhammad Ifte Khairul Islam, Md. Sadekur Rahman, Md. Abbas Ali Khan
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Word completion and word prediction are two important phenomena in typing that have extreme effect on aiding disable people and students while using keyboard or other similar devices. Such autocomplete technique also helps students significantly during learning process through constructing proper keywords during web searching. A lot of works are conducted for English language, but for Bangla, it is still very inadequate as well as the metrics used for performance computation is not rigorous...
Topics: Word prediction, Natural language processing, Language model, N-gram, Machine learning, Eager...