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College of Intelligent Computing

【AI Seminar】2026.11.03「From Cultural Archives to Judicial Reasoning: Structuring Text and Norms across Digital Humanities and Legal Informatics」-Prof. Chao-Lin Liu, NCCU College of Informatics

1. Speaker: Prof. Chao-Lin Liu, NCCU College of Informatics
2. Date & Time: Tuesday, November 3, 2026, 13:00-15:00
3. Venue: AI Lecture Hall,11th Floor-Management Building
4. Meeting Link: About the Speaker:
Professor Chao-Lin Liu is currently a distinguished professor in the Department of Computer Science, National Chengchi University. His research interests include natural language processing, cognitive processes, automated reasoning, machine learning theory, information retrieval, knowledge management systems, digital humanities, legal informatics, intelligent tutoring systems, intelligent transportation systems, decision support, and planning and diagnostic systems. He has served as Vice Dean of the College of Science, Vice Dean of the College of Informatics, and Chair of the Department of Computer Science at National Chengchi University. He has also held academic service positions, including President of the Taiwan Digital Humanities Society. Professor Liu has been a visiting scholar at the University of Michigan, Harvard University, and the University of California, Santa Barbara. He is committed to advancing academic research and social development through computational technologies and artificial intelligence. 
Lecture Abstract：
Generic statistical language models and unstructured text embeddings often struggle when applied to specialized Chinese corpora, where meaning is strictly governed by historical conventions or institutional norms. This talk presents an interdisciplinary journey across two distinct applications of computational semantics: discovering latent patterns in historical culture and enabling explainable decision-making in modern jurisprudence. The first half of the presentation focuses on digital humanities, demonstrating how computational methods overcome unpunctuated and irregular classical formats. We examine how linguistic heuristics and structural parallelism resolve classical poetry word segmentation, how large-scale alignment reveals diachronic stylometric patterns and text reuse across 2,000 years of poetic collections, and how language models and Conditional Random Fields extract prosopographical knowledge and demarcate biographical entries from historical local gazetteers (Difangzhi). The second half turns to legal informatics, exploring how domain priors transform unstructured prosecutorial and judicial documents into transparent, interpretable outputs. We demonstrate how statutory article co-citation networks establish objective case similarity in civil disputes; how deconstructing criminal fraud indictments into statutory constitutive elements yields explainable case analogies aligned with professional legal judgment; how structured prompt frameworks guide large language models through multi-cause concurrence and penalty comparisons; and how procedural trajectories can quantify case disputability and litigation risk. Together, these case studies demonstrate that computational semantics achieves its highest reliability not by treating language as generic token distributions, but by formalizing the structural and normative logic of the target domain. 
Lecture Abstract： Generic statistical language models and unstructured text embeddings often struggle when applied to specialized Chinese corpora, where meaning is strictly governed by historical conventions or institutional norms. This talk presents an interdisciplinary journey across two distinct applications of computational semantics: discovering latent patterns in historical culture and enabling explainable decision-making in modern jurisprudence. The first half of the presentation focuses on digital humanities, demonstrating how computational methods overcome unpunctuated and irregular classical formats. We examine how linguistic heuristics and structural parallelism resolve classical poetry word segmentation, how large-scale alignment reveals diachronic stylometric patterns and text reuse across 2,000 years of poetic collections, and how language models and Conditional Random Fields extract prosopographical knowledge and demarcate biographical entries from historical local gazetteers (Difangzhi). The second half turns to legal informatics, exploring how domain priors transform unstructured prosecutorial and judicial documents into transparent, interpretable outputs. We demonstrate how statutory article co-citation networks establish objective case similarity in civil disputes; how deconstructing criminal fraud indictments into statutory constitutive elements yields explainable case analogies aligned with professional legal judgment; how structured prompt frameworks guide large language models through multi-cause concurrence and penalty comparisons; and how procedural trajectories can quantify case disputability and litigation risk. Together, these case studies demonstrate that computational semantics achieves its highest reliability not by treating language as generic token distributions, but by formalizing the structural and normative logic of the target domain.
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