Big Data Analytics using Machine Learning Techniques

Mittal, Shweta; Sangwan, Om Prakash

doi:10.1109/confluence.2019.8776614

Cited by 13 publications

(7 citation statements)

References 19 publications

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“…A complete study of big data analysis tools and techniques has been presented by Mittal & Sangwan (2019) . The authors focused on studying machine learning techniques for big data analysis.…”

Section: Background and Related Workmentioning

confidence: 99%

Artificial intelligence approaches and mechanisms for big data analytics: a systematic study

Rahmani

Azhir

Ali

et al. 2021

PeerJ Computer Science

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Recent advances in sensor networks and the Internet of Things (IoT) technologies have led to the gathering of an enormous scale of data. The exploration of such huge quantities of data needs more efficient methods with high analysis accuracy. Artificial Intelligence (AI) techniques such as machine learning and evolutionary algorithms able to provide more precise, faster, and scalable outcomes in big data analytics. Despite this interest, as far as we are aware there is not any complete survey of various artificial intelligence techniques for big data analytics. The present survey aims to study the research done on big data analytics using artificial intelligence techniques. The authors select related research papers using the Systematic Literature Review (SLR) method. Four groups are considered to investigate these mechanisms which are machine learning, knowledge-based and reasoning methods, decision-making algorithms, and search methods and optimization theory. A number of articles are investigated within each category. Furthermore, this survey denotes the strengths and weaknesses of the selected AI-driven big data analytics techniques and discusses the related parameters, comparing them in terms of scalability, efficiency, precision, and privacy. Furthermore, a number of important areas are provided to enhance the big data analytics mechanisms in the future.

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Section: Background and Related Workmentioning

confidence: 99%

Artificial intelligence approaches and mechanisms for big data analytics: a systematic study

Rahmani

Azhir

Ali

et al. 2021

PeerJ Computer Science

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show abstract

“…Kolajo et al [5] presented a brief view about big data real-time analysis using continuous queries and achieved analysis on the fly within the stream. Mittal and Sangwan [6] have discussed several challenges that may take place while using traditional machine learning tools for big data analytics and its possible solutions. Yadranjiaghdam et al [7] constituted a brief survey on different methods in real-time analytics or stream analysis of the sheer volume data or big data in some specific domains of application.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Big Data Analysis Using Web Scraping in Apache Spark Environment: Case Study—Mobile Data Analysis from Flipkart

Ganguly

Parihar

Sivagami

2021

Artificial Intelligence and Technologies

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“…To analyze big data , institutions are increasingly using analytical solutions. These solutions include predictive and prescriptive analytical techniques [11] [12], often using AI and ML and Deep learning in particular, to understand and recommend actions based on the analysis of large volumes of data from multiple sources, internal or external.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Approach for Data Analysis and Decision Making in Big Data: A Case Study on E-commerce Industry

Zineb¹,

Rafalia²,

Abouchabaka³

2021

IJACSA

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A recent informational phenomenon has emerged as one of the considerable innovations in information systems, commonly referred to as "Big Data". The latter is currently trendy, both in academia and industry, and is used to describe a wide range of concepts, from data extraction, storage, and management, to data processing and analysis using well-known schemas, to extract patterns in hidden relationships in order to make better decisions and to derive new knowledge using analytical techniques and solutions. The technology that enables the potential of big data to be exploited is called "Big Data Analytics". Big data analytics is a major challenge that enables researchers, analysts and business users to make better decisions faster. Big Data became an important part of marketing research and marketing strategies. The e-commerce industry is one of the industries that currently benefits most from the potential of big data collection and analysis. This paper therefore aims to demonstrate the use of big data to understand customers and to improve and facilitate the decision making process. In this research, we apply multiple machine learning (ML) models on large dataset present in the e-commerce area by studying several practical cases on online markets.

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Big Data Analytics using Machine Learning Techniques

Cited by 13 publications

References 19 publications

Artificial intelligence approaches and mechanisms for big data analytics: a systematic study

Artificial intelligence approaches and mechanisms for big data analytics: a systematic study

Real-Time Big Data Analysis Using Web Scraping in Apache Spark Environment: Case Study—Mobile Data Analysis from Flipkart

An Intelligent Approach for Data Analysis and Decision Making in Big Data: A Case Study on E-commerce Industry

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