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Big data analytics has gained wide attention from both academia and industry as the demand for understanding trends in massive datasets increases. Recent developments in sensor networks, cyber-physical systems...
Recent developments in sensor networks and mobile computing led to a huge increase in data generated that need to be processed and analyzed efficiently. In this context, many distributed data mining algorithms...
The purpose of this work is to identify and analyze the oscillation of sentiments expressed by users of the Twitter social media through their direct replies to posts by user @jdoriajr that took place before, ...
Data validation is about verifying the correctness of data. When organisations update and refine their data transformations to meet evolving requirements, it is imperative to ensure that the new version of a w...
Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topi...
Moving objects such as people, animals, and vehicles have generated a large amount of spatiotemporal data by using location-capture technologies and mobile devices. This collected data needs to be processed, v...
No sleep! No sick days! No Holidays! alongside 24/7 around the clock tireless work, welcome to the world of Artificial Intelligence, how can humans match the phenomena of AI. Humanity is in the grip of an unst...
Pattern mining is a powerful tool for analysing big datasets. Temporal datasets include time as an additional parameter. This leads to complexity in algorithmic formulation, and it can be challenging to proces...
We study the the spread and adoption of libraries within Python projects hosted in public software repositories on GitHub. By modelling the use of Git pull, merge, commit, and other actions as deliberate cogni...
Despite the well-documented and numerous recent successes of deep learning, the application of standard deep architectures to many classification problems within empirical software engineering remains problema...
Hive has long been one of the industry-leading systems for Data Warehousing in Big Data contexts, mainly organizing data into databases, tables, partitions and buckets, stored on top of an unstructured distrib...
The global popularity of social media platforms has given rise to unprecedented amounts of data, much of which reflects the thoughts, opinions and affective states of individual users. Systematic explorations ...
Today, the diagnosis of Alzheimer’s disease (AD) or mild cognitive impairment (MCI) has attracted the attention of researchers in this field owing to the increase in the occurrence of the diseases and the need...
We address the problem of detecting highly raised crowd density in situations such as indoor dance events. We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi loc...
The publication and dissemination of raw data are crucial elements in commercial, academic, and medical applications. With an increasing number of open platforms, such as social networks and mobile devices fro...
Due to their conceptual simplicity and flexibility, non-parametric mixture models are widely used to identify latent clusters in data. However, when it comes to Big Data, such as Landsat imagery, such model fi...
Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking t...
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imb...
Prevention of hospital readmissions has the potential of providing better quality of care to the patients and deliver significant cost savings. A review of existing readmission analysis frameworks based on dat...
There has recently been a conscious push for cities across the globe to be smart and even smarter and thus more sustainable by developing and implementing big data technologies and their applications across va...
Critical systems that produce big data streams can require human operators to monitor these event streams for changes of interest. Automated systems which oversee many tasks can still have a need for the ‘huma...
The goal of this paper is to reduce the classification (inference) complexity of tree ensembles by choosing a single representative model out of ensemble of multiple decision-tree models. We compute the simila...
This study represents an efficient method for extracting product aspects from customer reviews and give solutions for inferring aspect ratings and aspect weights. Aspect ratings often reflect the user’s satisf...
The United States healthcare system produces an enormous volume of data with a vast number of financial transactions generated by physicians administering healthcare services. This makes healthcare fraud diffi...
As Big Data processing often takes a long time and needs a lot of resources, sampling and approximate computing techniques may be used to generate a desired Quality of Result. On the other hand, due to not con...
The Internet of Things (IoT) facilitates creation of smart spaces by converting existing environments into sensor-rich data-centric cyber-physical systems with an increasing degree of automation, giving rise t...
In the age of data driven solution, the customer demographic attributes, such as gender and age, play a core role that may enable companies to enhance the offers of their services and target the right customer...
Nature create variables using its character component, and variables are sharing characters from a vary small to relatively large scale. This results, variables to have from a vary different to a more similar ...
Deep Learning is an increasingly important subdomain of artificial intelligence, which benefits from training on Big Data. The size and complexity of the model combined with the size of the training dataset ma...
Currently, the data to be explored and exploited by computing systems increases at an exponential rate. The massive amount of data or so-called “Big Data” put pressure on existing technologies for providing sc...
Global environmental pollution caused by human activities has become a threat to public health. Children are especially susceptible to adverse environmental conditions owing to their unique physiological and b...
Diabetes is a chronic disease or group of metabolic disease where a person suffers from an extended level of blood glucose in the body, which is either the insulin production is inadequate, or because the body...
Big Data analytics such as credit scoring and predictive analytics offer numerous opportunities but also raise considerable concerns, among which the most pressing is the risk of discrimination. Although this ...
Internet traffic measurement and analysis generate dataset that are indicators of usage trends, and such dataset can be used for traffic prediction via various statistical analyses. In this study, an extensive...
The Management of mobile networks has become so complex due to a huge number of devices, technologies and services involved. Network optimization and incidents management in mobile networks determine the level...
In many real-world contexts, there is a pressing need to automatically screen for potential perpetrators, such as school shooters, whose prevalence in the population is extremely low. We first explain one poss...
Annually, lots of research papers are published in scientific journals around the world. The knowledge of the status of research is a prerequisite for research planning and policy making. This type of knowledg...
This paper studies how the presence of universities and hospitals influences local home prices and rents. We analyze the data on ZIP code level and on the level of individual homes. Our ZIP code-level analysis...
Big data analytics is gaining substantial attention due to its innovative contribution to decision making and strategic development across the healthcare field. Therefore, this study explored the adoption mech...
The problem studied in this paper is the road insecurity, which is manifested by the big number of injuries and deaths recorded annually around the world. These victims of road accidents worry the whole commun...
In recent years, mobility data from smart cards, mobile phones and sensors have become increasingly available. However, they often lack some of the key information including the purposes of trips for each indi...
In addressing the challenge of Big Data Analytics, what has been of notable significance is the analysis of online search traffic data in order to analyze and predict human behavior. Over the last decade, sinc...
The present work is a part of the ESTenLigne project which is the result of several years of experience for developing e-learning in Sidi Mohamed Ben Abdellah University through the implementation of open, onl...
Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive productivity and profit through data-driven decision makin...
Using the theory of affordance from perceptual psychology and through discussion of literature within visual data mining and immersive analytics, a position for the multi-sensory representation of big data usi...
Measuring pairwise document similarity is an essential operation in various text mining tasks. Most of the similarity measures judge the similarity between two documents based on the term weights and the infor...
Big data encompasses social networking websites including Twitter as popular micro-blogging social media platform for a political campaign. The explosive Twitter data as a respond of the political campaign can...
Query processing based on labeling dynamic XML documents has gained more attention in the past several years. An efficient labeling scheme should provide small size labels keeping the simplicity of the exploit...
Regression trees (RTs) are simple, but powerful models, which have been widely used in the last decades in different scopes. Fuzzy RTs (FRTs) add fuzziness to RTs with the aim of dealing with uncertain environ...
Short term traffic forecasting is one of the important fields of study in the transportation domain. Short term traffic forecasting is very useful to develop a more advanced transportation system to control tr...
2022 Citation Impact
8.1 - 2-year Impact Factor
5.095 - SNIP (Source Normalized Impact per Paper)
2.714 - SJR (SCImago Journal Rank)
2023 Speed
56 days submission to first editorial decision for all manuscripts (Median)
205 days submission to accept (Median)
2023 Usage
2,559,548 downloads
280 Altmetric mentions
