AI-based experts' knowledge visualization of cultural heritage: A case study of Terracotta Warriors

2026-04-24

AI Summary

This study addresses the limitation of existing research, which predominantly focuses on isolated representations of individual Terracotta Warriors, thereby neglecting systematic analysis of their collective attribute distributions and interrelationships. To overcome this, the authors construct a comprehensive attribute dataset of the warriors from Pit No. 1 and propose a novel paradigm that treats the entire cohort as an integrated whole for attribute analysis and knowledge visualization. Leveraging generative adversarial networks (GANs) for data augmentation and employing AI-driven methods such as random forests to uncover latent feature correlations, the work achieves structured modeling and intuitive visualization of group-level characteristics. By shifting from an individual-centric to a collective-oriented approach, this research establishes a reproducible technical framework for representing the communal dimensions of cultural heritage.

Technology Category

• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Humans and AI: Understanding People, Theories, Concepts and Methods
• Data Mining & Knowledge Management: Data Visualization & Summarization

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Web Mining and Content Analysis: Web data visualization
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Advancements in 3D modeling,digital display technologies,and the growing availability of digital cultural heritage data have significantly improved the accuracy of heritage depictions and expanded opportunities for analysis.However,while many studies focus on presenting specific cultural heritage figurines,an often overlooked aspect is the visualization of the Terracotta Warriors as a unified entity.This involves concisely representing the distribution of features and their relationships,providing a clear and insightful presentation that engages practitioners, academics,and wider audiences.To tackle the challenges mentioned above,this research seeks to explore the application of AI methods in processing cultural heritage data.It aims to optimize and augment the dataset,analyze the distribution and relationships of various attributes, and interpret the analysis results through visualization techniques.The Terracotta Warriors,among China's most significant cultural heritages and renowned for their abundance,exquisite workmanship,and magnitude,are chosen as a case study.The contribution of this paper is primarily twofold.Firstly,we constructed a dataset of Terracotta Warriors from Pit No.1,detailing the attributes significant for identifying different Terracotta Warriors.Secondly,we employ various AI methods,such as generative adversarial network and random forest,to process and analyze these attributes,followed by visualizing the analysis results for an intuitive presentation.This study introduces a novel scheme for presenting information on a collection of cultural relics,offering a practical case for analyzing and visualizing the Terracotta Warriors'attributes as a whole entity,rather than showcasing individual relics'information in isolation.

Problem

• cultural heritage
• Terracotta Warriors
• knowledge visualization
• feature distribution
• relational representation

Innovation

• AI-based visualization
• cultural heritage analysis
• generative adversarial network
• attribute distribution
• Terracotta Warriors