An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters. - Peter Gronvall; Nathaniel Huber-Fliflet; Jianping Zhang 003; Robert Keeling; Robert Neary; Haozhen Zhao (IEEE BigData, 2018)

Empirical Evaluations of Seed Set Selection Strategies for Predictive Coding. - Christian J. Mahoney; Nathaniel Huber-Fliflet; Katie Jensen; Haozhen Zhao; Robert Neary; Shi Ye 002 (IEEE BigData, 2018)

Comparative Analysis of LLM-Generated Event Timeline Summarization for Legal Investigations. - Qiang Mao; Adam Dabrowski; Fusheng Wei; Eric Olson; Robert Neary; Jingchao Yang; Han Qin; Nathaniel Huber-Fliflet (IEEE Big Data, 2024)

Empirical Evaluation of Embedding Models in the Context of Text Classification in Document Review in Construction Delay Disputes. - Fusheng Wei; Robert Neary; Han Qin; Qiang Mao; Jianping Zhang 001 (IEEE Big Data, 2024)

A Hybrid Approach for Privilege Document Review: Rule-Based and Machine Learning. - Jingchao Yang; Adam Dabrowski; Robert Neary; Nathaniel Huber-Fliflet (IEEE Big Data, 2024)

Empirical Evaluation of Ensemble and Single Model Approaches for Multilingual Predictive Coding. - Jingchao Yang; Adam Dabrowski; Robert Neary; Nathaniel Huber-Fliflet; Fusheng Wei; Qiang Mao (IEEE Big Data, 2024)

Empirical Evaluation of Embedding Models in the Context of Text Classification in Document Review in Construction Delay Disputes. - Fusheng Wei; Robert Neary; Han Qin; Qiang Mao; Jianping Zhang 003 (CoRR, 2025)