Applied Advanced Analytics: 6th Iima International Conference on Advanced Data Analysis, Business Analytics and Intelligence

ISBN-13: 9789813366558 / Angielski / Twarda / 2021 / 234 str.

Arnab Kumar Laha

Spis treści

Part A: Expository Briefs

Chapter 1 : Shikha Verma_Data Streams

Chapter 2 : Pravida Raja_Robust Statistics

Chapter 3 : Arnab Kumar Laha_Functional Data Analysis

Chapter 4 : Murari Mitra_Reliability Shock Models and Applications

 

Part B: Artificial Intelligence Applications

Chapter 5: Sandip Pal, Amol A. Bhave and Kingshuk Banerjee_Explainable Artificial Intelligence Model: Analysis of Neural Network Parameters

Chapter 6 : Sayan Putatunda_Care2Vec: A Deep learning approach for the classification of self-care problems in physically disabled children

Chapter 7 : Abhishek Khushwaha, Saurav Chakravorty and Paulami Das_Style Scanner - Personalized visual search and recommendation

Chapter 8 : Sanjay Thawakar and Vibhu Srivastav_Artificial Intelligence based Cost Reduction for Customer Retention Management in the Indian Life Insurance Industry

 

Part C: Credit Risk Analytics

Chapter 9 : Shreya Piplani and Geetika Bansal_Optimization of Initial Credit Limit using comprehensive customer features

Chapter 10 : Aditi Singh and Nishtha Jain_Mitigating Agricultural Lending Risk: An advanced analytical approach

 

Part D: Analytics and Machine Learning in Retail

Chapter 11 : Seinjuti Chatterjee, Ravi Shankar Mishra, Sagar Raichandani and Prasad Joshi_Response prediction and ranking models for large scale E-commerce search

Chapter 12 : Akshay Jain, Shrey Jain and Nitin Merh_Application of Association Rule Mining in a clothing Retail Store

 

Part E: Analytics and Machine Learning in Operations

Chapter 13 : Rishabh Agrawal and R. P. Suresh_Improving Blast Furnace Operations using Advanced Analytics

Chapter 14 : Kalyani Dacha, Abir Sinha and Ramya Cherukupalli_Food Index Forecasting

Chapter 15 : R. Sujatha and B. Uma Maheswari_Implementing Learning Analytic Tools in Predicting Students’ Performance in a Business School

 

Part F : New Methodologies

Chapter 16 : Atanu Biswas_An optimal Response Adaptive Design for Multi Treatment Clinical Trials with Circular

Responses

Chapter 17 : Shyamal Ghosh, Priyanka Majumder and Murari Mitra_Stochastic comparisons of systems with heterogeneous log-logistic components

Chapter 18 : Biswaroop Mukherjee and Abhishek Halder_Stacking With Dynamic Weights on Base Models

 

Part G: Applications in Finance and Economics

Chapter 19 : Avijit Ghosh , Aditya Chourasiya , Lakshay Bansal and Abhijeet Chandra_Connectedness of Markets with Heterogeneous Agents and the Information Cascades

Chapter 20 : Rudra P. Pradhan_Role of Infrastructure and Taxation on Economic Growth of Middle Income Countries

Chapter 21 : Stuti Mohan and Swati Verma_Comparative study of different Benchmarking techniques: Evaluating performance of the Indian banking industry

O autorze

Arnab Kumar Laha is Professor of Production and Quantitative Methods (P&QM) at Indian Institute of Management Ahmedabad. He takes a keen interest in understanding how analytics, machine learning, and artificial intelligence can be leveraged to solve complex problems of business and society. He has published his research in national and international journals of repute, authored a popular book on analytics and an edited book volume published by Springer. He has been named as one of the "20 Most Prominent Analytics and Data Science Academicians in India" by Analytics India Magazine in 2018.

Blurb

This book covers several new areas in the growing field of analytics with some innovative applications in different business contexts. The book is conceptually divided in seven parts. The first part gives expository briefs on some topics of current academic and practitioner interests, such as data streams,  binary prediction and reliability shock models. In the second part, the contributions look at artificial intelligence applications with chapters related to explainable AI,  personalized search and recommendation, and customer retention management. The third part deals with credit risk analytics, with chapters on optimization of credit limits and mitigation of agricultural lending risks. In its fourth part, the book explores analytics and data mining in the retail context. In the fifth part, the book presents some applications of analytics to operations management. This part has chapters related to improvement of furnace operations, forecasting food indices and analytics for improving student learning outcomes. The sixth part has contributions related to adaptive designs in clinical trials, stochastic comparisons of systems with heterogeneous components and stacking of models. The seventh and final part contains chapters related to finance and economics topics, such as role of infrastructure and taxation on economic growth of countries and connectedness of markets with heterogenous agents, The different themes ensure that the book would be of great value to practitioners, post-graduate students, research scholars and faculty teaching advanced business analytics courses.