Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning

• URL: http://arxiv.org/abs/2501.13252v1
• Date: Wed, 22 Jan 2025 22:18:50 GMT
• Title: Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning
• Authors: Ali Nazari, Michael Weiss,
• Abstract summary: This study presents a method for exploring advancements in a specific technological domain.<n>It combines topic modeling, expert input, and reinforcement learning (RL)<n>The framework provides a robust tool for exploring evolving technological landscapes.
• Score: 0.48342038441006807
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This study presents a method for exploring advancements in a specific technological domain. It combines topic modeling, expert input, and reinforcement learning (RL). The proposed approach has three key steps: (1) generate aspect-based topic models using expert-weighted keywords to emphasize critical aspects, (2) analyze similarities and entropy changes by comparing topic distributions across iterative models, and (3) refine topic selection using reinforcement learning (RL) with a modified reward function that integrates changes in topic divergence and similarity across iterations. The method is tested on quantum communication documents with a focus on advances in cryptography and security protocols. The results show the method's effectiveness and can identify, rank, and track trends that match expert input. The framework provides a robust tool for exploring evolving technological landscapes.

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