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Conversational Artificial Intelligence
book

Conversational Artificial Intelligence

by Romil Rawat, Rajesh Kumar Chakrawarti, Sanjaya Kumar Sarangi, Anand Rajavat, Mary Sowjanya Alamanda, Kotagiri Srividya, K. Sakthidasan Sankaran
March 2024
Intermediate to advanced content levelIntermediate to advanced
800 pages
28h 48m
English
Wiley-Scrivener
Content preview from Conversational Artificial Intelligence

9Identification of User Preference Using Human–Computer Interaction Technologies and Design of Customized Reporting for Business Analytics Using Ranking Consistency Index

Martin Aruldoss1*, Miranda Lakshmi Travis2 and Prasanna Venkatesan Venkatasamy3

1Department of Computer Science, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India

2PG and Research Department of Computer Science, St. Joseph’s College (Autonomous), Cuddalore, Tamil Nadu, India

3Dept. of Banking Technology, Pondicherry University, Puducherry, India

Abstract

Business intelligence (BI) provides a comprehensive solution for organizations to make better decisions. Reporting is one of the important functionalities of BI, which provides vital information for decision-making. Due to the extreme growth of information, designing customized reporting according to user level and requirement in an organization is the present challenge of the information analysis system. To develop a well-organized customized reporting, user preference with respect to different criteria (conditions) should be identified. Multi-criteria reporting (MCR) is one of the special kinds of customized reporting that customizes the information according to user preference and criteria. In MCR, preference of information differs from one user to another user and it is identified using Multi-Criteria Decision Making (MCDM) techniques. General Fuzzy TOPSIS (GFTOPSIS) is one of the MCDM techniques, and its working procedure consists of a ...

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Publisher Resources

ISBN: 9781394200566Purchase Link