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2020 – today
- 2021
[c23]Haozhen Zhao, Shi Ye
, Jingchao Yang:
An Empirical Study on Transfer Learning for Privilege Review. IEEE BigData 2021: 2729-2733- [c22]Haozhen Zhao, Fusheng Wei, Hilary Quatinetz, Han Qin, Adam Dabrowski:
Use Image Clustering to Facilitate Technology Assisted Review. IEEE BigData 2021: 2734-2736 - [i15]Christian J. Mahoney, Katie Jensen, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye:
Application of Deep Learning in Recognizing Bates Numbers and Confidentiality Stamping from Images. CoRR abs/2102.02995 (2021) - [i14]Rishi Chhatwal, Robert Keeling, Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Haozhen Zhao:
CNN Application in Detection of Privileged Documents in Legal Document Review. CoRR abs/2102.04845 (2021) - [i13]Haozhen Zhao, Fusheng Wei, Hilary Quatinetz, Han Qin, Adam Dabrowski:
Use Image Clustering to Facilitate Technology Assisted Review. CoRR abs/2112.08604 (2021) - [i12]Haozhen Zhao, Shi Ye, Jingchao Yang:
An Empirical Study on Transfer Learning for Privilege Review. CoRR abs/2112.08606 (2021) - 2020
- [c21]Rishi Chhatwal, Robert Keeling, Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Haozhen Zhao:
CNN Application in Detection of Privileged Documents in Legal Document Review. IEEE BigData 2020: 1485-1492 - [c20]Christian J. Mahoney, Katie Jensen, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye:
Application of Deep Learning in Recognizing Bates Numbers and Confidentiality Stamping from Images. IEEE BigData 2020: 2127-2130
2010 – 2019
- 2019
- [c19]Christian J. Mahoney, Jianping Zhang, Nathaniel Huber-Fliflet, Peter Gronvall, Haozhen Zhao:
A Framework for Explainable Text Classification in Legal Document Review. IEEE BigData 2019: 1858-1867 - [c18]Robert Keeling, Rishi Chhatwal, Nathaniel Huber-Fliflet, Jianping Zhang, Fusheng Wei, Haozhen Zhao, Ye Shi, Han Qin:
Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review. IEEE BigData 2019: 2038-2042 - [c17]Nathaniel Huber-Fliflet, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye, Amy Tsang:
Image Analytics for Legal Document Review : A Transfer Learning Approach. IEEE BigData 2019: 4325-4328 - [c16]Christian J. Mahoney, Nathaniel Huber-Fliflet, Haozhen Zhao, Jianping Zhang, Peter Gronvall, Shi Ye:
Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding. LegalAIIA@ICAIL 2019: 23-31 - [i11]Christian J. Mahoney, Nathaniel Huber-Fliflet, Katie Jensen, Haozhen Zhao, Robert Neary, Shi Ye:
Empirical Evaluations of Seed Set Selection Strategies for Predictive Coding. CoRR abs/1903.08816 (2019) - [i10]Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Empirical Evaluations of Preprocessing Parameters' Impact on Predictive Coding's Effectiveness. CoRR abs/1904.01718 (2019) - [i9]Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Empirical Evaluations of Active Learning Strategies in Legal Document Review. CoRR abs/1904.01719 (2019) - [i8]Rishi Chhatwal, Peter Gronvall, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding. CoRR abs/1904.01721 (2019) - [i7]Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Robert Keeling, Robert Neary, Haozhen Zhao:
An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters. CoRR abs/1904.01722 (2019) - [i6]Fusheng Wei, Han Qin, Shi Ye, Haozhen Zhao:
Empirical Study of Deep Learning for Text Classification in Legal Document Review. CoRR abs/1904.01723 (2019) - [i5]Han Qin, Kit Riehle, Haozhen Zhao:
Using Google Analytics to Support Cybersecurity Forensics. CoRR abs/1904.01725 (2019) - [i4]Christian J. Mahoney, Nathaniel Huber-Fliflet, Haozhen Zhao, Jianping Zhang, Peter Gronvall, Shi Ye:
Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding. CoRR abs/1906.04367 (2019) - [i3]Robert Keeling, Rishi Chhatwal, Nathaniel Huber-Fliflet, Jianping Zhang, Fusheng Wei, Haozhen Zhao, Shi Ye, Han Qin:
Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review. CoRR abs/1912.09499 (2019) - [i2]Christian J. Mahoney, Jianping Zhang, Nathaniel Huber-Fliflet, Peter Gronvall, Haozhen Zhao:
A Framework for Explainable Text Classification in Legal Document Review. CoRR abs/1912.09501 (2019) - [i1]Nathaniel Huber-Fliflet, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye, Amy Tsang:
Image Analytics for Legal Document Review: A Transfer Learning Approach. CoRR abs/1912.12169 (2019) - 2018
- [c15]Rishi Chhatwal, Peter Gronvall, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding. IEEE BigData 2018: 1905-1911 - [c14]Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Robert Keeling, Robert Neary, Haozhen Zhao:
An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters. IEEE BigData 2018: 3282-3291 - [c13]Christian J. Mahoney, Nathaniel Huber-Fliflet, Katie Jensen, Haozhen Zhao, Robert Neary, Shi Ye:
Empirical Evaluations of Seed Set Selection Strategies for Predictive Coding. IEEE BigData 2018: 3292-3301 - [c12]Fusheng Wei, Han Qin, Shi Ye, Haozhen Zhao:
Empirical Study of Deep Learning for Text Classification in Legal Document Review. IEEE BigData 2018: 3317-3320 - 2017
- [c11]Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Empirical evaluations of active learning strategies in legal document review. IEEE BigData 2017: 1428-1437 - [c10]Han Qin, Kit Riehle, Haozhen Zhao:
Using google analytics to support cybersecurity forensics. IEEE BigData 2017: 3831-3834 - 2016
- [c9]Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao:
Empirical evaluations of preprocessing parameters' impact on predictive coding's effectiveness. IEEE BigData 2016: 1394-1401 - 2014
- [c8]Haozhen Zhao:
Sharding for literature search via cutting citation graphs. IEEE BigData 2014: 77-79 - [c7]Haozhen Zhao, Xiaohua Hu:
Language Model Document Priors based on Citation and Co-citation Analysis. BIR@ECIR 2014: 29-36 - [c6]Haozhen Zhao, Xiaohua Hu:
Drexel at TREC 2014 Federated Web Search Track. TREC 2014 - 2012
- [c5]Xia Lin, Mi Zhang, Haozhen Zhao, Jan W. Buzydlowski:
Multi-view of the ACM classification system. JCDL 2012: 397-398 - 2010
- [c4]Haozhen Zhao, Xia Lin:
A comparison of mapping algorithms for author co-citation data analysis. ASIST 2010: 1-3
2000 – 2009
- 2008
- [c3]Jiepu Jiang, Wei Lu, Haozhen Zhao:
CSIR at TREC 2008 Expert Search Task: Modeling Expert Evidence in Expertise Retrieval. TREC 2008 - 2007
- [c2]Haozhen Zhao, Zhicheng Luo, Wei Lu:
WHU at Blog Track 2007. TREC 2007 - 2006
- [c1]Wei Lu, Stephen E. Robertson, Andrew MacFarlane, Haozhen Zhao:
Window-based Enterprise Expert Search. TREC 2006
Coauthor Index
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