Nathaniel Huber-Fliflet

According to our database1, Nathaniel Huber-Fliflet authored at least 17 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Bibliography

2023
An Empirical Analysis of Text Segmentation for BERT Classification in Extended Documents.
Proceedings of the IEEE International Conference on Big Data, 2023

Empirical Study of LLM Fine-Tuning for Text Classification in Legal Document Review.
Proceedings of the IEEE International Conference on Big Data, 2023

Exploring Approaches to Optimize the Performance of Predictive Coding on Multilanguage Data Sets.
Proceedings of the IEEE International Conference on Big Data, 2023

Explainable Text Classification for Legal Document Review in Construction Delay Disputes.
Proceedings of the IEEE International Conference on Big Data, 2023

Exploring the Performance Impacts of Training Predictive Models with Inclusive Email Threads.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Explainable Text Classification Techniques in Legal Document Review: Locating Rationales without Using Human Annotated Training Text Snippets.
Proceedings of the IEEE International Conference on Big Data, 2022

Integration of Rule-Based Reasoning and Transfer Learning in Legal Document Review.
Proceedings of the IEEE International Conference on Big Data, 2022

2020
CNN Application in Detection of Privileged Documents in Legal Document Review.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding.
Proceedings of the First Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2019) the 17th International Conference on Artificial Intelligence and Law (ICAIL 2019), 2019

A Framework for Explainable Text Classification in Legal Document Review.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Image Analytics for Legal Document Review : A Transfer Learning Approach.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Empirical Evaluations of Seed Set Selection Strategies for Predictive Coding.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Empirical evaluations of active learning strategies in legal document review.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Empirical evaluations of preprocessing parameters' impact on predictive coding's effectiveness.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016


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