Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Nathaniel Huber-Fliflet"'
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e35322af8b6879276a7027165df549c4
https://doi.org/10.1109/bigdata55660.2022.10020626
https://doi.org/10.1109/bigdata55660.2022.10020626
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0470fb5dd6a889b7fdd094f1ae648d3c
https://doi.org/10.1109/bigdata55660.2022.10020392
https://doi.org/10.1109/bigdata55660.2022.10020392
Autor:
Rishi Chhatwal, Haozhen Zhao, Robert Keeling, Jianping Zhang, Peter Gronvall, Nathaniel Huber-Fliflet
Publikováno v:
IEEE BigData
Protecting privileged communications and data from disclosure is paramount for legal teams. Legal advice, such as attorney-client communications or litigation strategy are typically exempt from disclosure in litigations or regulatory events and are v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f810956e4860f242ea1dd24222f7ac3
Publikováno v:
IEEE BigData
Companies regularly spend millions of dollars producing electronically-stored documents in legal matters. Recently, parties on both sides of the 'legal aisle' are accepting the use of machine learning techniques like text classification to cull massi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c77230db6c17dd4d6d877f841b60a5d
http://arxiv.org/abs/1912.09501
http://arxiv.org/abs/1912.09501
Publikováno v:
IEEE BigData
Though technology assisted review in electronic discovery has been focusing on text data, the need of advanced analytics to facilitate reviewing multimedia content is on the rise. In this paper, we present several applications of deep learning in com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d0431f22cc539e73c90867bd8e11d30
https://doi.org/10.1109/bigdata47090.2019.9006551
https://doi.org/10.1109/bigdata47090.2019.9006551
Publikováno v:
IEEE BigData
Predictive coding, once used in only a small fraction of legal and business matters, is now widely deployed to quickly cull through increasingly vast amounts of data and reduce the need for costly and inefficient human document review. Previously, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de0e2fd2d2904baaab940e7403f1eb66
http://arxiv.org/abs/1904.01718
http://arxiv.org/abs/1904.01718
Autor:
Rishi Chhatwal, Haozhen Zhao, Peter Gronvall, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang
Publikováno v:
IEEE BigData
In today's legal environment, lawsuits and regulatory investigations require companies to embark upon increasingly intensive data-focused engagements to identify, collect and analyze large quantities of data. When documents are staged for review the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a463c5781f7af9e1ed4b4e6050567cfa
http://arxiv.org/abs/1904.01721
http://arxiv.org/abs/1904.01721
Publikováno v:
IEEE BigData
One type of machine learning, text classification, is now regularly applied in the legal matters involving voluminous document populations because it can reduce the time and expense associated with the review of those documents. One form of machine l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb37923d49341f456c4b8102777c5957
http://arxiv.org/abs/1904.01719
http://arxiv.org/abs/1904.01719
Autor:
Han Qin, Nathaniel Huber-Fliflet, Robert Keeling, Ye Shi, Fusheng Wei, Haozhen Zhao, Rishi Chhatwal, Jianping Zhang
Publikováno v:
IEEE BigData
Research has shown that Convolutional Neural Networks (CNN) can be effectively applied to text classification as part of a predictive coding protocol. That said, most research to date has been conducted on data sets with short documents that do not r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::025ae01a21a50ea3fbc74738dc66c504
Autor:
Nathaniel Huber-Fliflet, Haozhen Zhao, Katie Jensen, Christian J. Mahoney, Shi Ye, Robert Neary
Publikováno v:
IEEE BigData
Training documents have a significant impact on the performance of predictive models in the legal domain. Yet, there is limited research that explores the effectiveness of the training document selection strategy - in particular, the strategy used to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb81cc3b1991ea2f2f1e913e6351ddcb
https://doi.org/10.1109/bigdata.2018.8622075
https://doi.org/10.1109/bigdata.2018.8622075