Publications
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Persian language teaching
Linguistic Data-Driven Approach to Persian Language Pedagogy: Practical Application to Compound Verbs
Karine Megerdoomian
There exists a significant disconnect between linguistic research and pedagogical practice in the Persian classroom. Discover what this means for Persian and multilingual, low-resource NLP.
Presentation
2025
Persian NLP
AI-enabled narrative analysis for Persian and Kurdish
Karine Megerdoomian and Emmanuel Garcia
Narratives are foundational to human expression across cultures. Discover what this means for Persian and multilingual, low‑resource NLP.
Technical Report
2024
Responsible AI
Responsible AI Mitigation Strategies
Karine Megerdoomian
Responsible AI is an umbrella term used to describe an approach that considers the business, legal, and ethical choices in the design, development, deployment, and adoption of AI. Learn how this advances responsible, transparent, and inclusive AI practice.
Proceedings Article
2023
Narrative Analytics
Induction of Narrative Models for Legal Case Elicitation
Karl Branting, Sarah McLeod, Bryant Park and Karine Megerdoomian
This paper proposes a new computational architecture for narrative-driven case elicitation, describes six new legal narrative corpora, and evaluates two different approaches to creating legal narrative schemas, the first using language models, and the second using event sequence alignment. See how the authors model structure, events, and time in real‑world texts.
Technical Report
2023
Narrative Analytics
Advanced Narrative Analytics System Infrastructure (ANAnSI)
Karine Megerdoomian and Charles Horowitz
This paper provides an in-depth description of the Advanced Narrative Analytics System Infrastructure (ANAnSI), which performs content extraction and detailed narrative analytics for knowledge discovery within a distributed high-performance system infrastructure. See how the authors model structure, events, and time in real‑world texts.
Journal Article
2023
Narrative Analytics, Health & AI
Automated Extraction of Substance Use and Co-occurring Disorders from Probation Records
Karine Megerdoomian, Charles E. Horowitz and Amy B. Marsh
The authors describe the application of advanced Natural Language Processing (NLP) and Artificial Intelligence (AI) methods to automatically discover and analyze important information from text. See how the authors model structure, events, and time in real‑world texts.
Technical Report
2023
Scientometrics
S&T@Scale: Understanding the global science and technology landscape
Jason Duncan, Chris Giannella, Karine Megerdoomian, Ransom Winder
Over the past several decades, the S&T landscape has transformed into a more geographically distributed, more interconnected, and more dynamic arena for collaboration and knowledge exchange. Read for methods, evaluations, and why the findings matter for scalable AI systems.
Proceedings Article
2022
Narrative Analytics
A Comprehensive Evaluation and Correction of the TimeBank Corpus
Mustafa Ocal, Antonela Radas, Jared Hummer, Karine Megerdoomian and Mark A. Finlayson
TimeML is an annotation scheme for capturing temporal information in text. See how the authors model structure, events, and time in real‑world texts.
Technical Report
2022
Narrative Analytics
Automated Knowledge Discovery for Online Child Pornography Offender Risk Assessment
Karine Megerdoomian, Amy Marsh and Charles Horowitz
The effectiveness of sex offender management policies and supervision approaches relies on the ability of criminal justice professionals to accurately differentiate sexual offenders according to their risk to recidivate. Read for methods, evaluations, and why the findings matter for scalable AI systems.
Book Chapter
2020
Persian language teaching, Heritage speakers
Linguistic Competence of Persian Heritage Versus Second Language Speakers
Karine Megerdoomian
This chapter provides a review of the research previously conducted on Persian heritage linguistics, with a focus on the domains of phonology, morphology and syntax. Discover what this means for Persian and multilingual, low‑resource NLP.
Proceedings Article
2019
Narrative Analytics
Automated Narrative Extraction from Administrative Records
Karine Megerdoomian, Karl Branting, Charles E. Horowitz, Amy B. Marsh, Nick Modly, Stacy J. Petersen, Eric O. Scott and Sujit B. Wariyar
The U. See how the authors model structure, events, and time in real‑world texts.
Book Chapter
2019
Persian NLP
Computational Linguistics
Karine Megerdoomian
This chapter introduces the fields of Computational Linguistics (CL)—the computational modelling of linguistic representations and theories—and Natural Language Processing (NLP)—the design and implementation of tools for automated language understanding and production—and discusses some of the existing tensions between the formal approach to linguistics and the. Discover what this means for Persian and multilingual, low‑resource NLP.