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Given the growing importance of customer behavior in the business market nowadays, telecom operators focus not only on customer profitability to increase market share but also on highly loyal customers as well...
This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers ...
Pageview is the most popular webpage analytic metric in all sectors including blogs, business, e-commerce, education, entertainment, research, social media, and technology. To perform deeper analysis, addition...
This paper proposes a novel algorithm for optimizing decision variables with respect to an outcome variable of interest in complex problems, such as those arising from big data. The proposed algorithm builds o...
Augmented reality, computer vision and other (e.g. network functions, Internet-of-Things (IoT)) use cases can be realised in edge computing environments with machine learning (ML) techniques. For realisation o...
Multi activity-multi object recognition (MAMO) is a challenging task in visual systems for monitoring, recognizing and alerting in various public places, such as universities, hospitals and airports. While bot...
In Machine Learning, if one class has a significantly larger number of instances (majority) than the other (minority), this condition is defined as class imbalance. With regard to datasets, class imbalance can bi...
Negative screening is one method to avoid interactions with inappropriate entities. For example, financial institutions keep investment exclusion lists of inappropriate firms that have environmental, social, a...
Big data is one of the most recent business and technical issues in the age of technology. Hundreds of millions of events occur every day. The financial field is deeply involved in the calculation of big data ...
Stock-market prediction using machine-learning technique aims at developing effective and efficient models that can provide a better and higher rate of prediction accuracy. Numerous ensemble regressors and cla...
Emotion recognition using brain signals has the potential to change the way we identify and treat some health conditions. Difficulties and limitations may arise in general emotion recognition software due to t...
Nowadays, a huge amount of data are generated, often in very short time intervals and in various formats, by a number of different heterogeneous sources such as social networks and media, mobile devices, inter...
Shares choice to enter a portfolio is a good topic in finance and management, as it affects the portfolio performance which is managed by a Fund Manager. In this research, we aim to create an artificial neural...
In recent years, entrepreneurship has become an important issue due to national economic development and the contribution of society. Data with a hierarchical structure received more attention and occur freque...
One of the ways of increasing recognition ability in classification problem is removing outlier entries as well as redundant and unnecessary features from training set. Filtering and feature selection can have...
The analysis of big data is a fundamental challenge for the current and future stream of data coming from many different sources. Geospatial data is one of the sources currently less investigated. A typical ex...
Launching new products in the consumer electronics market is challenging. Developing and marketing the same in limited time affect the sustainability of such companies. This research work introduces a model th...
Big data innovation is a key instrument for economic and social development and for the creation of new business opportunities. This study analyzes the patenting activities of global jurisdictions in the field...
Sensor data quality plays a vital role in Internet of Things (IoT) applications as they are rendered useless if the data quality is bad. This systematic review aims to provide an introduction and guide for res...
Online social networks have established virtual platforms enabling people to express their opinions, interests and thoughts in a variety of contexts and domains, allowing legitimate users as well as spammers a...
Telecom Companies logs customer’s actions which generate a huge amount of data that can bring important findings related to customer’s behavior and needs. The main characteristics of such data are the large nu...
Nowadays, the fast rate of technological advances, such as cloud computing, has led to the rapid growth of the Data Center (DC) market as well as their power consumption. Therefore, DC power management has bec...
Scholars have been increasingly calling for innovative research in the organizational sciences in general, and the information systems (IS) field in specific, one that breaks from the dominance of gap-spotting...
MapReduce is used within the Hadoop framework, which handles two important tasks: mapping and reducing. Data clustering in mappers and reducers can decrease the execution time, as similar data can be assigned ...
Much corporate organization nowadays implement enterprise resource planning (ERP) to manage their business processes. Because the processes run continuously, ERP produces a massive log of processes. Manual obs...
Increased sensing data in the context of the Internet of Things (IoT) necessitates data analytics. It is challenging to write applications for Big Data systems due to complex, highly parallel software framewor...
Value Chain has been considered as a key model for managing efficiently value creation processes within organizations. However, with the digitization of the end-to-end processes which began to adopt data as a ...
Explosive performance and memory space growth in computing machines, along with recent specialization of deep learning models have radically boosted the role of images in semantic pattern recognition. In the s...
The Retraction Note to this article has been published in Journal of Big Data 2020 7:40
Sentiment analysis is recognized as one of the most important sub-areas in Natural Language Processing (NLP) research, where understanding implicit or explicit sentiments expressed in social media contents is ...
Medical image classification plays an essential role in clinical treatment and teaching tasks. However, the traditional method has reached its ceiling on performance. Moreover, by using them, much time and eff...
The analysis and processing of big data are one of the most important challenges that researchers are working on to find the best approaches to handle it with high performance, low cost and high accuracy. In t...
Internet of Things (IoT) is a new paradigm that has changed the traditional way of living into a high tech life style. Smart city, smart homes, pollution control, energy saving, smart transportation, smart ind...
In building management, energy optimization is one of the main concern that needs to be automated. For automation, an intelligent system needs to be developed. However, an intelligent system needs to be traine...
With the rapid development of smart grids and increasing data collected in these networks, analyzing this massive data for applications such as marketing, cyber-security, and performance analysis, has gained p...
This paper presents a lifelong learning framework which constantly adapts with changing data patterns over time through incremental learning approach. In many big data systems, iterative re-training high dimen...
Severe class imbalance between majority and minority classes in Big Data can bias the predictive performance of Machine Learning algorithms toward the majority (negative) class. Where the minority (positive) clas...
Due to the advent of new technologies, devices, and communication tools such as social networking sites, the amount of data produced by mankind is growing rapidly every year. Big data is a collection of large ...
Many data analytics algorithms are originally designed for in-memory data. Parallel and distributed computing is a natural first remedy to scale these algorithms to “Big algorithms” for large-scale data. Advan...
A number of technologies enabled by Internet of Thing (IoT) have been used for the prevention of various chronic diseases, continuous and real-time tracking system is a particularly important one. Wearable med...
Feature selection is mainly used to lessen the dispensation load of data mining models. To condense the time for processing voluminous data, parallel processing is carried out with MapReduce (MR) technique. Ho...
The no-schema approach of NoSQL document stores is a tempting solution for importing heterogenous geospatial data to a spatial database. However, this approach means sacrificing the benefits of RDBMSes, such a...
In this paper, a quantitative temporal and spatial analysis of the dynamics of hot topics popularity in Micro-blogging system was provided. Firstly, the popularity time series of 1167 hot topics were counted a...
In the era of big data applications, the demand for more sophisticated data centers and high-performance data processing mechanisms is increasing drastically. Data are originally stored in storage systems. To ...
Many systems can be represented as networks or graph collections of nodes joined by edges. The social structures in these networks can be investigated using graph theory through a process called social network...
The input to a machine learning model is a one-dimensional feature vector. However, in recent learning models, such as convolutional and recurrent neural networks, two- and three-dimensional feature tensors ca...
In this paper we are proposing an adaptive and real-time approach to resolve real-time financial data integration latency problems and semantic heterogeneity. Due to constraints that we have faced in some proj...
A scalable graphical method is presented for selecting and partitioning datasets for the training phase of a classification task. For the heuristic, a clustering algorithm is required to get its computation co...
Smartphones are considered as one of the most essential and highly personal devices of individuals in our current world. Due to the popularity of context-aware technology and recent developments in smartphones...
The Hadoop distributed file system (HDFS) is responsible for storing very large data-sets reliably on clusters of commodity machines. The HDFS takes advantage of replication to serve data requested by clients ...
In recent years, the rapid growth of the Internet has led to creation of massively large graphs. Since databases have become very large nowadays, they cannot be processed by a simple machine at an acceptable t...
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
