IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Comprehensive Contemplation of Probabilistic Aspects in Intelligent Analytics

Comprehensive Contemplation of Probabilistic Aspects in Intelligent Analytics
View Sample PDF
Author(s): Neeti Sangwan (USICT, GGS Indraprastha University and MSIT, New Delhi, India)and Vishal Bhatnagar (Department of Computer Science and Engineering, Ambedkar Institute of Advanced Communication Technologies and Research, New Delhi, India)
Copyright: 2020
Volume: 11
Issue: 1
Pages: 26
Source title: International Journal of Service Science, Management, Engineering, and Technology (IJSSMET)
Editor(s)-in-Chief: Ahmad Taher Azar (College of Computer & Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia & Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt)and Ghazy Assassa (Benha University, Egypt)
DOI: 10.4018/IJSSMET.2020010108

Purchase

View Comprehensive Contemplation of Probabilistic Aspects in Intelligent Analytics on the publisher's website for pricing and purchasing information.

Abstract

In Big Data analysis, the application of machine learning has proven to be a revolutionary. The systematic review of literature shows that research has been carried out on the domain of big data analytics particularly text analytics with the inclusion of machine learning approaches. This extensive survey deals with the data at hand that provides different ways and issues while combining the machine learning approaches with the text. During the course of the survey, various publications in the field of synchronous application of machine learning in text analytics were searched and studied. Classification framework is proposed as the contribution of machine learning in text analytics. A classification framework represented the various application areas to motivate researchers for future research on the application of two emerging technologies.

Related Content

Yuan Ren. © 2024. 8 pages.
Hadeel Al-Obaidy, Aysha Ebrahim, Ali Aljufairi, Ahmed Mero, Omar Eid. © 2024. 19 pages.
Anna M. Segooa, Billy M. Kalema. © 2024. 27 pages.
Muath AlShaikh, Waleed Alsemaih, Sultan Alamri, Qusai Ramadan. © 2024. 19 pages.
Jon A. Chilingerian, Mitchell P. V. Glavin. © 2024. 27 pages.
Osama R. S. Ramadan, Mohamed Yasin I. Afifi, Ahmed Yahya. © 2024. 19 pages.
Utsav Upadhyay, Alok Kumar, Gajanand Sharma, Ashok Kumar Saini, Varsha Arya, Akshat Gaurav, Kwok Tai Chui. © 2024. 30 pages.
Body Bottom