An Exploration of Pattern Mining with ChatGPT

TL;DR

This paper explores using ChatGPT for pattern mining through an eight-step collaborative process, demonstrating how AI and human insights can jointly extract and describe patterns, especially in integrating LLMs with data sources.

Contribution

It introduces a novel eight-step process for pattern mining with ChatGPT and proposes adding component affordances as a new pattern description element.

Findings

Successful creation of a pattern language for LLM integration

Demonstrated practical application of the process

Highlighted the importance of component affordances in patterns

Abstract

This paper takes an exploratory approach to examine the use of ChatGPT for pattern mining. It proposes an eight-step collaborative process that combines human insight with AI capabilities to extract patterns from known uses. The paper offers a practical demonstration of this process by creating a pattern language for integrating Large Language Models (LLMs) with data sources and tools. LLMs, such as ChatGPT, are a new class of AI models that have been trained on large amounts of text, and can create new content, including text, images, or video. The paper also argues for adding affordances of the underlying components as a new element of pattern descriptions. The primary audience of the paper includes pattern writers interested in pattern mining using LLMs.