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Keyword: Machine learningTowards a Documents Processing Tool using Traceability Information Retrieval and Content Recognition Through Machine Learning in a Big Data Context
In 1980, an application was developed to track, manage and store documents in electronic format. Scan technology has enabled organizations to digitize papers for easier document storage and tracking. Document management tools have since developed by introducing new functionalities, related to security, users services, workflow and audit. Our research is part of the context of…
Read MoreExtending the Classifier Algorithms in Machine Learning to Improve the Performance in Spoken Language Understanding Systems Under Deficient Training Data
One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge…
Read MoreOvermind: A Collaborative Decentralized Machine Learning Framework
This paper is an extension of work originally presented in PM2.5 Prediction-based Weather Forecast Information and Missingness Challenges: A Case Study Industrial and Metropolis Areas, which focused on imputation algorithm to solve missingness challenge and demonstrated a basic prediction system to prove the proposed algorithm, II-MPA. Distributed and decentralized systems, recently, have been proven for…
Read MoreInterpretation of Machine Learning Models for Medical Diagnosis
Machine learning has been dramatically advanced over several decades, from theory context to a general business and technology implementation. Especially in healthcare research, it is obvious to perceive the scrutinizing implementation of machine learning to warranty the rewarded benefits in early disease detection and service recommendation. Many practitioners and researchers have eventually recognized no absolute…
Read MoreSupervised Machine Learning Based Medical Diagnosis Support System for Prediction of Patients with Heart Disease
Application in the field of medical development has always been one of the most important research areas. One of these medical applications is the early prediction system for heart diseases especially; coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support system is to detect atherosclerosis at the earlier stages to…
Read MoreMachine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read MoreCustomer Satisfaction Recognition Based on Facial Expression and Machine Learning Techniques
Nowadays, Customer satisfaction is important for businesses and organizations. Manual methods exist, namely surveys and distributing questionnaires to customers. However, marketers and businesses are looking for quick ways to get effective and efficient feedback results for their potential customers. In this paper, we propose a new method for facial emotion detection to recognize customer’s satisfaction…
Read MoreOptimization of the Procedures for Checking the Functionality of the Greek Railways: Data Mining and Machine Learning Approach to Predict Passenger Train Immobilization
Information is the driving force of businesses because it can ensure the ability of knowledge and prediction. The railway industry produces a huge volume of data, with the proper processing of them and the use of innovative technology, there is the possibility of beneficial information to be provided which constitute the deciding factor for the…
Read MoreFraud Detection Call Detail Record Using Machine Learning in Telecommunications Company
Fraud calls have a serious impact on telecommunications operator revenues. Fraud detection is very important because service providers can feel a significant loss of income. We conducted a fraud research case study on one of the operators that experienced fraud in 2009 and 2018. Call Detail Record (CDR) containing records of customer conversations such as…
Read MoreEfficient Discretization Approaches for Machine Learning Techniques to Improve Disease Classification on Gut Microbiome Composition Data
The human gut environment can contain hundreds to thousands bacterial species which are proven that they are associated with various diseases. Although Machine learning has been supporting and developing metagenomic researches to obtain great achievements in personalized medicine approaches to improve human health, we still face overfitting issues in Bioinformatics tasks related to metagenomic data…
Read MoreMachine Learning Model to Identify the Optimum Database Query Execution Platform on GPU Assisted Database
With the current amount of data nowadays, the need for processing power has vastly grown. By relying on CPU processing power, current processing power is depending on the frequency and parallelism of the current CPU device. This means this method will lead to increased power consumption. Current research has shown that by utilize the power…
Read MoreIntrusion Detection in Cyber Security: Role of Machine Learning and Data Mining in Cyber Security
In recent years, cyber security has been received interest from several research communities with respect to Intrusion Detection System (IDS). Cyber security is “a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc.” An IDS is a software…
Read MoreClassification Model of Contact Center Customers Emails Using Machine Learning
E-mail is one of the media services used at the contact center. The challenge faced by e-mail services is how to handle e-mails that enter large quantities every day efficiently to provide fast and appropriate service to customers. The purpose of this study is to find which method has the best accuracy in classifying emails…
Read MoreQuranic Reciter Recognition: A Machine Learning Approach
Recitation and listening of the Holy Quran with Tajweed is an essential activity as a Muslim and is a part of the faith. In this article, we use a machine learning approach for the Quran Reciter recognition. We use the database of Twelve Qari who recites the last Ten Surah of Quran. The twelve Qari…
Read MoreEstimating Academic results from Trainees’ Activities in Programming Exercises Using Four Types of Machine Learning
Predicting trainees’ final academic results in the early stage of programming class is a significant mission in the field of learning analytics. Performing exercises in programming class is hard and it takes a lot of time for trainees. For this reason, careful support with trainees are offered in many classes through classroom assistants (CAs). Even…
Read MoreMachine Learning Applied to GRBAS Voice Quality Assessment
Voice problems are routinely assessed in hospital voice clinics by speech and language therapists (SLTs) who are highly skilled in making audio-perceptual evaluations of voice quality. The evaluations are often presented numerically in the form of five-dimensional ‘GRBAS’ scores. Computerised voice quality assessment may be carried out using digital signal processing (DSP) techniques which process…
Read MoreEmotional Impact of Suicide on Active Witnesses: Predicting with Machine Learning
Predicting the impact of suicide on incidental witnesses at an early stage helps to avert the possible side effect. When suicide is committed in public, incidental observers are left to grapple with it. In many cases, these incidental witnesses tend to experience the emotional side effect with time. In this study, we employed a Machine…
Read MoreA Machine Learning Framework Using Distinctive Feature Extraction for Hand Gesture Recognition
There are more than 7billion people in the world where there are around 500 million people in the world who are denied from normal lifestyle due to physical and mental issue. It is completely fair to say that every person deserves to enjoy a normal lifestyle. While physically and mentally challenged people find suitable way…
Read MorePredicting Smoking Status Using Machine Learning Algorithms and Statistical Analysis
Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting…
Read MoreImproving System Reliability Assessment of Safety-Critical Systems using Machine Learning Optimization Techniques
Quality assurance of modern-day safety-critical systems is continually facing new challenges with the increase in both the level of functionality they provide and their degree of interaction with their environment. We propose a novel selection method for black-box regression testing on the basis of machine learning techniques for increasing testing efficiency. Risk-aware selection decisions are…
Read MoreMachine Learning framework for image classification
Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of Features method used to find image representation. Class prediction accuracy of varying classifiers algorithms is measured on Caltech 101 images. For feature extraction functions we evaluate…
Read MoreApplying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction
Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future…
Read MoreA Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
With the abundance of Internet and electronic devices bullying has moved its place from schools and backyards into cyberspace; to be now known as Cyberbullying. Cyberbullying is affecting a lot of children around the world, especially Arab countries. Thus concerns from cyberbullying are rising. A lot of research is ongoing with the purpose of diminishing…
Read MoreA Machine Learning based Framework for Parameter based Multi-Objective Optimisation of Video CODECs
All multimedia devices now incorporate video CODECs that comply with international video coding standards such as H.264 / MPEG4-AVC and the new High Efficiency Video Coding Standard (HEVC), otherwise known as H.265. Although the standard CODECs have been designed to include algorithms with optimal efficiency, a large number of coding parameters can be used to…
Read MoreUse of machine learning techniques in the prediction of credit recovery
This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s…
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