In this paper, we provide an overview of state-of-the-art research issues and achievements in the field analytics over big data, extend discussion to multidimensional data as well, by highlighting open problems actual trends. Our analytical contribution is finally completed several novel directions arising field, which plays a leading role next-generation Data Warehousing OLAP research.

Privacy and security of Big Data is gaining momentum in the research community, also due to emerging technologies like Cloud Computing, analytics engines social networks. In response this novel challenge, several privacy big data models, techniques algorithms have been proposed recently, mostly adhering algorithmic paradigms or model-oriented paradigms. Following major trend, paper we provide an overview state-of-the-art issues achievements field data, by highlighting open problems actual...

In this paper, we highlight open problems and actual research trends in the field of Data Warehousing OLAP over Big Data, an emerging term research. We also derive several novel directions arising field, put emphasis on possible contributions to be achieved by future efforts.

Recently, a great deal of interest for Big Data has risen, mainly driven from widespread number research problems strongly related to real-life applications and systems, such as representing, modeling, processing, querying mining massive, distributed, large-scale repositories (mostly being unstructured nature). Inspired by this main trend, in paper we discuss three important aspects research, namely OLAP over Data, Posting, Privacy Data. We also depict future directions, hence implicitly...

Business analytics use techniques from data science, mining, artificial intelligence (especially, machine learning), mathematics and statistics to gain insights understanding on the performance of business processes. The gained knowledge help driving planning. As employees play important roles in process, having a tool classify predict their wage levels is desirable. Such classification prediction enables public or private sector offer competitive wages for recruiting retaining employees. In...

In the current era of big data, huge quantities valuable which may be different levels veracity, are being generated at a rapid rate. Embedded into these data implicit, previously unknown and potentially useful information knowledge that can discovered by science solutions, apply techniques like mining. There has been trend more collections have made openly available in science, government non-profit organizations so people could collaboratively study analysis open data. this article, we...

In this paper we present how fake news spread in the current online social networks. We discuss existing network technologies such as influence maximization, information diffusion, and epidemiological models contributes to creation spreading. Solutions reducing spreading of are also reviewed. make recommendations regarding future areas research field.

With the rapid technological advancement, security has become a major issue due to increase in malware activity that poses serious threat and safety of both computer systems stakeholders. To maintain stakeholders, particularly, end users security, protecting data from fraudulent efforts is one most pressing concerns. A set malicious programming code, scripts, active content, or intrusive software designed destroy intended programs mobile web applications referred as malware. According study,...

Abstract We analyze a case study in the field of smart agriculture exploiting Explainable AI (XAI) approach, that aims to provide interpretations and explanations behaviour systems. The regards multiclass classification problem on Crop Recommendation dataset. original task is prediction most adequate crop, according seven features. In addition predictions, two well-known XAI approaches have been used order obtain models: SHAP ( SH apley A dditive Ex P lanations), LIME (Local Interpretable...

With technological advancements, big data can be easily generated and collected in many applications. Embedded these are useful information knowledge that discovered by machine learning mining models, techniques or algorithms. A rich source of is stock exchange. The ability to effectively predict future prices improves the economic growth development a country. Traditional linear approaches for prediction (e.g., Kalman filters) may not practical handling like due highly nonlinear chaotic...

Since its debut in May 2016, Overwatch has quickly become a popular team-based online video game. Despite the popularity of Overwatch, many new players—who join game unsure how to compete with game’s veterans—feel overwhelmed vast knowledge required properly play at higher skill levels. In this paper, data mining algorithm is designed and developed for clustering visualization cyber-physical world boundary. Scientifically, uses affinity propagation two-dimensional graphs visualizing data....

This paper explores the convergence of Data Warehousing, OLAP and data-intensive Cloud Infrastructures in context so-called analytics over Big Data. The briefly reviews some state-of-the-art proposals, highlights open research issues and, finally, it draws possible directions this scientific field.

Social influence is referred to as the phenomenon that one's opinions or behaviors be affected by others. Nowadays, potential impact of social analysis (SIA) significant. For example, SIA applications can include viral marketing, online content recommendation. Convention uses hand-crafted features and requires domain expert knowledge. Such an approach not scalable introduces a high cost. To overcome these disadvantages, deep learning based approaches was introduced. One most recent DeepInf,...

In the current era of big data, a huge amount data has been generated and collected from wide variety rich sources. Embedded in these are useful information valuable knowledge. An example is healthcare epidemiological such as related to patients who suffered epidemic diseases like coronavirus disease 2019 (COVID-19). Knowledge discovered helps researchers, epidemiologists policy makers get better understanding disease, which may inspire them come up ways detect, control combat disease. As "a...

In the current technological era, huge amounts of big data are generated and collected from a wide variety rich sources. These can be different levels veracity in sense that some them precise while others imprecise uncertain. Embedded these useful information valuable knowledge to discovered. An example is healthcare epidemiological such as related patients who suffered epidemic diseases like coronavirus disease 2019 (COVID-19). Knowledge discovered data-via science techniques machine...

In recent years, artificial intelligence (AI) and its subarea of deep learning have drawn the attention many researchers. At same time, advances in technologies enable generation or collection large amounts valuable data (e.g., sensor data) from various sources different applications, such as those for Internet Things (IoT), which turn aims towards development smart cities. With availability sources, information fusion is demand effective integration big data. this article, we present an...

Traditional network intrusion detection approaches encounter feasibility and sustainability issues to combat modern, sophisticated, unpredictable security attacks. Deep neural networks (DNN) have been successfully applied for problems. The optimal use of DNN-based classifiers requires careful tuning the hyper-parameters. Manually hyperparameters is tedious, time-consuming, computationally expensive. Hence, there a need an automatic technique find best DNN in detection. This paper proposes...

With the ever-growing concern for internet security, field of quantum cryptography emerges as a promising solution enhancing security networking systems. In this paper, 20 notable papers from leading conferences and journals are reviewed categorized based on their focus various aspects cryptography, including key distribution, bit commitment, post-quantum counterfactual distribution. The paper explores motivations challenges employing addressing privacy concerns along with existing...