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In this research various concepts from network theory and topic modelling are combined, to provision a temporal network of associated topics. This solution is presented as a step-by-step process to facilitate ...
The number of Web APIs for accessing information and services is continuously increasing, and yet, no tools exist to automate the time-consuming and error-prone process of invoking those APIs and composing the...
In severely imbalanced datasets, using traditional binary or multi-class classification typically leads to bias towards the class(es) with the much larger number of instances. Under such conditions, modeling a...
Sleep loss has been linked to heart disease, diabetes, cancer, and an increase in accidents, all of which are among the leading causes of death in the United States. Population-scale sleep studies have the pot...
Many researchers have recently considered patients’ health and provided an optimal and appropriate solution. With the advent of technologies such as cloud computing, Internet of Things and 5G, information can ...
Detecting and delineating hot spots in data from radiation sensors is required in applications ranging from monitoring large geospatial areas to imaging small objects in close proximity. This paper describes a...
In this paper, we propose a novel deep learning-based feature learning architecture for object classification. Conventionally, deep learning methods are trained with supervised learning for object classificati...
Assessing equity in treatment of a subpopulation often involves assigning numerical “scores” to all individuals in the full population such that similar individuals get similar scores; matching via propensity ...
If a decision tree is constructed through a series of locally optimal solutions, such as the Greedy method, overfitting to the data is likely to occur. In order to avoid overfitting, many previous research hav...
Context-aware system (CAS) is a system that can understand the context of a given situation and either share this context with other systems for their response or respond by itself. In surgery, these systems a...
The diversity and sheer increase in the number of connected Internet of Things (IoT) devices have brought significant concerns associated with storing and protecting a large volume of IoT data. Storage volume ...
Process discovery helps companies automatically discover their existing business processes based on the vast, stored event log. The process discovery algorithms have been developed rapidly to discover several ...
Duplicate record is a common problem within data sets especially in huge volume databases. The accuracy of duplicate detection determines the efficiency of duplicate removal process. However, duplicate detecti...
The ever increasing sophistication of intrusion approaches has led to the dire necessity for developing Intrusion Detection Systems with optimal efficacy. However, existing Intrusion Detection Systems have bee...
Data mining techniques were used to investigate the use of knowledge extraction in predicting customer churn in insurance companies. Data were included from a health insurance company for providing insight int...
Gene expression provides a means for an organism to produce gene products necessary for the organism to live. Variation in the significant gene expression levels can distinguish the gene and the tissue in whic...
The design used to create labelled data for training prediction models from observational healthcare databases (e.g., case-control and cohort) may impact the clinical usefulness. We aim to investigate hypothet...
This article proposes a new parallel performance model for different workloads of Spark Big Data applications running on Hadoop clusters. The proposed model can predict the runtime for generic workloads as a f...
Network Anomaly Detection is still an open challenging task that aims to detect anomalous network traffic for security purposes. Usually, the network traffic data are large-scale and imbalanced. Additionally, ...
As the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment ...
As one of the most popular financial market instruments, the stock has formed one of the most massive and complex financial markets in the world. It could handle millions of transactions within a short period ...
Arguments facilitate humans to deliver their ideas. The outcome of the discussion heavily relies on the validity of the argument. If an argument is well-composed, it is more effective to grasp the core idea be...
Road traffic accidents (RTA) are commonly encountered incidents that can cause injuries, death, and property damage to members of society. Ethiopia is one of the highest incident rates of road traffic accident...
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with...
In this paper, we introduce three new implementations of non-native methods for storing RDF data. These methods named RDFSPO, RDFPC and RDFVP, are based respectively on the statement table, property table and ...
The early detection of the coronavirus disease 2019 (COVID-19) outbreak is important to save people’s lives and restart the economy quickly and safely. People’s social behavior, reflected in their mobility dat...
Recent advances in Internet applications have facilitated information spreading and, thanks to a wide variety of mobile devices and the burgeoning 5G networks, users easily and quickly gain access to informati...
Most of the current cancer treatment approaches are invasive along with a broad spectrum of side effects. Furthermore, cancer drug resistance known as chemoresistance is a huge obstacle during treatment. This ...
Nowadays, urban data such as demographics, infrastructure, and criminal records are becoming more accessible to researchers. This has led to improvements in quantitative crime research for predicting future cr...
This paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social medi...
Large data requirements are often the main hurdle in training neural networks. Convolutional neural network (CNN) classifiers in particular require tens of thousands of pre-labeled images per category to appro...
To address the challenges of big data analytics, several works have focused on big data optimization using metaheuristics. The constraint satisfaction problem (CSP) is a fundamental concept of metaheuristics t...
Nowadays a large amount of data is originated by complex systems, such as social networks, transportation systems, computer and service networks. These systems can be modeled by using graphs and studied by exp...
A key challenge in mining social media data streams is to identify events which are actively discussed by a group of people in a specific local or global area. Such events are useful for early warning for acci...
Computer networks target several kinds of attacks every hour and day; they evolved to make significant risks. They pass new attacks and trends; these attacks target every open port available on the network. Se...
The public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big d...
Evaluating the exact first derivative of a feedforward neural network (FFNN) output with respect to the input feature is pivotal for performing the sensitivity analysis of the trained neural network with respe...
With the rapid growth in the amount of video data, efficient video indexing and retrieval methods have become one of the most critical challenges in multimedia management. For this purpose, Content-Based Video...
Many algorithms have proposed to solve the association rule learning problem. However, most of these algorithms suffer from the problem of scalability either because of tremendous time complexity or memory usa...
Brain computer interface (BCI) systems have been regarded as a new way of communication for humans. In this research, common methods such as wavelet transform are applied in order to extract features. However,...
Feature selection is a pre-processing technique used to remove unnecessary characteristics, and speed up the algorithm's work process. A part of the technique is carried out by calculating the information gain...
Social media postings are increasingly being used in modern days disaster management. Along with the textual information, the contexts and cues inherent in the images posted on social media play an important r...
Data-driven innovation is propelled by recent scientific advances, rapid technological progress, substantial reductions of manufacturing costs, and significant demands for effective decision support systems. T...
The process of big data handling refers to the efficient management of storage and processing of a very large volume of data. The data in a structured and unstructured format require a specific approach for ov...
Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degr...
Social media platforms have become fundamental tools for sharing information during natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events Detection on sOcial Media During Disasters...
The Covid-19 pandemic that began in the city of Wuhan in China has caused a huge number of deaths worldwide. Countries have introduced spatial restrictions on movement and social distancing in response to the ...
The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-touris...
Big Data is an essential research area for governments, institutions, and private agencies to support their analytics decisions. Big Data refers to all about data, how it is collected, processed, and analyzed ...
Class imbalance is an important consideration for cybersecurity and machine learning. We explore classification performance in detecting web attacks in the recent CSE-CIC-IDS2018 dataset. This study considers ...
Citation Impact
10.835 - 2 Year Impact Factor (2021)
4.661 - Source Normalized Impact per Paper (SNIP)
2.592 - SCImago Journal Rank (SJR)
14.4 - CiteScore
Speed
94 days to first decision for all manuscripts (Median)
106 days to first decision for reviewed manuscripts only (Median)
Usage
2,250,289 downloads (2022)
982 Altmetric mentions (2021)
