Is There a Gender Bias in Personas Generated by ChatGPT?

For this blog posting, we experiment with different ChatGPT prompts and glimpse gender biases in output. The motivation of this experiment is to inspect if ChatGPT propagates gender biases. Gender biases in ChatGPT have been noticed before. For example, Ivana Bartoletti, Director of Women Leading in AI, asked Chat GPT-4 to write “a story about…… Continue reading Is There a Gender Bias in Personas Generated by ChatGPT?

Analytics Systems are Sporadic Use but Constant Collection

Analytics systems are information services that are used to analyze and interpret data to gain insights, identify patterns, and support decision-making processes. Analytics systems are one of the unique information services that are a combination of sporadic use but require constant data collection. Sporadic or occasional use information systems are information services that are used…… Continue reading Analytics Systems are Sporadic Use but Constant Collection

Will They Take This Offer? A Machine Learning Price Elasticity Model for Predicting Upselling Acceptance of Premium Airline Seating

Employing customer information from one of the world’s largest airline companies, we develop a price elasticity model (PREM) using machine learning to identify customers likely to purchase an upgrade offer from economy to premium class and predict a customer’s acceptable price range. A simulation of 64.3 million flight bookings and 14.1 million email offers over three years…… Continue reading Will They Take This Offer? A Machine Learning Price Elasticity Model for Predicting Upselling Acceptance of Premium Airline Seating

Unlock the Power of BERT for Binary Text Classification

In the world of natural language processing, one of the most important tasks is binary text classification. Binary text classification is the process of classifying text into two distinct classes. For example, a binary classifier could classify an email into either spam or not.  A new deep learning tool called BERT (Bidirectional Encoder Representations from…… Continue reading Unlock the Power of BERT for Binary Text Classification

Demystifying Language Models: The Case of BERT’s Usage in Solving Classification Problems

Newcomers to the field of Artificial Intelligence (AI) often see the term ‘language model’ tossed around when discussing Natural Language Processing (NLP) tasks without any proper clarification of its importance and usage in solving real-world problems. So, this tutorial blogpost aims at demystifying language models by defining what a language model is, describing the common…… Continue reading Demystifying Language Models: The Case of BERT’s Usage in Solving Classification Problems

Big Data Fallacy

Big Data Fallacy. The law of large numbers argues that the sample’s mean approaches the sample population’s actual average as a sample size increases. This concept is often, either implicitly or explicitly, taken as a justification as to why ‘big data’ (i.e., millions or billions of samples) cannot be wrong. However, there are contrary arguments and…… Continue reading Big Data Fallacy

What Happened to Strategic Segmentation?

Introduction and the Research Problem Angus Jenkinson proposed a study titled “What happened to strategic segmentation?” published in the Journal of Direct, Data and Digital Market Practice in 2009. The study discusses segmentation performed from descriptive, predictive, and operational analysis presents the gold standard for a market analysis for marketers. The author highlights that 20…… Continue reading What Happened to Strategic Segmentation?

Manual and Automatic Methods for User Needs Detection in Requirements Engineering: Key Concepts and Challenges

User needs inform designers and developers of essential functionalities for requirements engineering. In this work, we summarize key concepts and challenges relating to manual and automatic user needs detection methods. We discuss six challenges with manual and eight challenges with automated methods. A. Challenges of Manual Methods • A01: Limited sample sizes. • A02: Budgetary…… Continue reading Manual and Automatic Methods for User Needs Detection in Requirements Engineering: Key Concepts and Challenges

Soft Computing: Impactful Tools in Customer Segmentation

Introduction Knowing your customers is essential to a successful business. It helps establish a rapport between the customers and the business, and makes the customers personally attached to what they are buying. Customer segmentation helps organizations recognize customers with similarities as a group rather than as individuals. It makes it easy to serve consumers efficiently…… Continue reading Soft Computing: Impactful Tools in Customer Segmentation

Customer Segmentation in a Large Database of an Online Customized Fashion Business

Introduction and the Research Problem The paper “Customer segmentation in a large database of an online customized fashion business” (2015) by Pedro Quelhas Brito, Carlos Soares, Sergio Almeida, Ana Monte and Michel Byvoet sets out to explore how data mining (DM) techniques can be used to drive marketing approaches in highly customized industries, such as…… Continue reading Customer Segmentation in a Large Database of an Online Customized Fashion Business