The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Significance of Natural Language Processing in Data Analysis Using Business Intelligence
|
|
Author(s): Jayashree Rajesh (School of Computing Sciences, VISTAS, India)and Priya Chitti Babu (School of Computing Sciences, VISTAS, India)
Copyright: 2021
Pages: 20
Source title:
Deep Natural Language Processing and AI Applications for Industry 5.0
Source Author(s)/Editor(s): Poonam Tanwar (Manav Rachna International Institute of Research and Studies, India), Arti Saxena (Manav Rachna International Institute of Research and Studies, India)and C. Priya (Vels Institute of Science, Technology, and Advanced Studies, India)
DOI: 10.4018/978-1-7998-7728-8.ch009
Purchase
|
Abstract
In the current machine-centric world, humans expect a lot from machines right from waking us up. We expect them to do activities like reminding us on traffic, tracking of appointments, etc. The smart devices we have with us are creating a constructive impact on our day-to-day lives. Many of us have not thought about the communication between ourselves and the devices we have and the language we use for communication. Natural language processing runs behind all these activities and is currently playing a vital role with respect to the communication with humans with the use of virtual assistants like Alexa, Siri, and search engines like Bing, Google, etc. This implies that we are talking with the machines as if they are human. The advanced natural language processing techniques have drastically modified the way to discover and interact with data. In the recent world, the same advanced techniques are primarily used in the data analysis using NLP in business intelligence tools. This chapter elaborates the significance of natural language processing in business intelligence.
Related Content
|
Wasswa Shafik.
© 2024.
25 pages.
|
|
Muthmainnah Muthmainnah, Eka Apriani, Prodhan Mahbub Ibna Seraj, Ahmed J. Obaid, Ahmad M. Al Yakin.
© 2024.
17 pages.
|
|
Arkar Htet, Sui Reng Liana, Theingi Aung, Amiya Bhaumik.
© 2024.
26 pages.
|
|
Shwetha Baliga, Harshith K. Murthy, Apoorv Sadhale, Dhruti Upadhyaya.
© 2024.
18 pages.
|
|
Manoj Kumar Pandey, Jyoti Upadhyay.
© 2024.
21 pages.
|
|
R. Angeline, S. Aarthi, Rishabh Jain, Muzamil Faisal, Abishek Venkatesan, R. Regin.
© 2024.
16 pages.
|
|
Gagan Deep, Jyoti Verma.
© 2024.
20 pages.
|
|
|