Top Research Papers on Big Data Analytics

This book covers big data analytics techniques, e.g. optimization, SVM, feature selection, and their use in business, engineering and healthcare.

The state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, are investigated.

The research positively confirmed that medical facilities in Poland are moving towards data-based healthcare, together with its benefits, and clearly shows that the decisions made in medical facilities are highly data-driven.

It emerges that big data analysis (BDA), traditional marketing analysis (TMA) and big data system quality (BDSQ) are significant determinants of new product development (NPD) success and the BDA and TMA significantly affect the BDSQ.

Continued advancement of sensors has led to an ever-increasing amount of data of various physical nature to be acquired from production lines. As rich information relevant to the machines and processes are embedded within these "big data", how to effectively and efficiently discover patterns in the big data to enhance productivity and economy has become both a challenge and an opportunity. This paper discusses essential elements of and promising solutions enabled by data science that are critical to processing data of high volume, velocity, variety, and low veracity, towards the creation of ad...

An overview of Big Data Analytics as a crucial process in many fields and sectors is presented and issues such as analytics cycle, analytics benefits and the movement from ETL to ELT paradigm as a result of Big data analytics in Cloud are discussed.

A comprehensive review of associated topics such as the concept of big data, model driven and data driven methodologies and the challenges and opportunities for future research are highlighted.

This paper proposes a review of related works to IoT, Big Data Analytics in smart buildings, revealing new trends of understanding information technologies to integrate in this sector.

A new binary variant of the wrapper feature selection grey wolf optimization and particle swarm optimization is proposed, and the K-nearest neighbor classifier with Euclidean matrices is used to find the optimal solutions.

This paper tenders a systematic literature review method for big data analytic approaches in weather forecasting (published between 2014 and August 2020) and presents a comparison of the aforementioned categories regarding accuracy, scalability, execution time, and other Quality of Service factors.

The findings from this study suggest that applications of BDA in healthcare can be observed from five perspectives, namely, health awareness among the general public, interactions among stakeholders in the healthcare ecosystem, hospital management practices, treatment of specific medical conditions, and technology in healthcare service delivery.

Big Data applications in CI processes within organizations within organizations are examined by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations.

It is posits that to successfully use data for competitive advantage, tourism and hospitality organisations need to solely expand compliance-based data governance frameworks to frameworks that include more effective privacy and ethics data solutions.

A neural network-based model is designed to diagnose and predict the pandemic, which can facilitate medical staff and predict pandemic using neural networks and also compare the results with other machine learning algorithms.

A comprehensive bibliometric analysis of applications of big data analytics in enterprises with a total of 1727 articles from the Scopus database identified four major thematic areas in the extant literature.

A modern data-driven decision theory, DECAS, is proposed, which extends upon classical decision theory by proposing three main claims: (1) (big) data and analytics (machine) should be considered as separate elements; (2) collaboration between the (human) decision maker and the analytics ( machine) can result in a collaborative rationality, extending beyond the classically defined bounded rationality.

It is proposed that data envelopment analysis (DEA) should be viewed as a method (or tool) for data-oriented analytics in performance evaluation and benchmarking and shown that network DEA is related to the value dimension of big data.

The 6G-based big data analysis technology can significantly improve large-scale IoT devices’ access success rate and enable the system to meet the requirements of low energy consumption and high accesssuccess rate, significant for research on more devices‘ access data analysis.

A comprehensive literature review of the current and emerging paradigms for Big educational data, including predictive analytics, learning analytics including collaborative, behavior, personal learnings and assessment, and technological challenges for Big data in education is presented.

ABSTRACT Operational risk management (ORM) is critical for any organization, and in the big data era, analytical tools for operational risk management are evolving faster than ever. This paper examines recent developments in academic ORM literature from the data analytics perspective. We focus on identifying present trends in ORM related to various types of natural and man‐made disasters that have been challenging all aspects of life. Although we examine the broader operations management (OM) literature, we keep the focus on the articles published in the well‐regarded OM journals, including bo...