Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Lewis, David D."'
Autor:
Yang, Eugene, Lewis, David D.
Technology-assisted review (TAR) is an important industrial application of information retrieval (IR) and machine learning (ML). While a small TAR research community exists, the complexity of TAR software and workflows is a major barrier to entry. Dr
Externí odkaz:
http://arxiv.org/abs/2202.11827
Content moderation (removing or limiting the distribution of posts based on their contents) is one tool social networks use to fight problems such as harassment and disinformation. Manually screening all content is usually impractical given the scale
Externí odkaz:
http://arxiv.org/abs/2108.12752
Technology-assisted review (TAR) workflows based on iterative active learning are widely used in document review applications. Most stopping rules for one-phase TAR workflows lack valid statistical guarantees, which has discouraged their use in some
Externí odkaz:
http://arxiv.org/abs/2108.12746
Technology-assisted review (TAR) refers to human-in-the-loop active learning workflows for finding relevant documents in large collections. These workflows often must meet a target for the proportion of relevant documents found (i.e. recall) while al
Externí odkaz:
http://arxiv.org/abs/2106.09871
Technology-assisted review (TAR) refers to human-in-the-loop machine learning workflows for document review in legal discovery and other high recall review tasks. Attorneys and legal technologists have debated whether review should be a single iterat
Externí odkaz:
http://arxiv.org/abs/2106.09866
Technology-assisted review (TAR) refers to iterative active learning workflows for document review in high recall retrieval (HRR) tasks. TAR research and most commercial TAR software have applied linear models such as logistic regression to lexical f
Externí odkaz:
http://arxiv.org/abs/2105.01044
Autor:
Lewis, David D.
Thesis (M.S.)--North Carolina State University.
Includes vita. Includes bibliographical references (p. 60).
Includes vita. Includes bibliographical references (p. 60).
Autor:
Lewis, David D., Gale, William A.
The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual. An algorithm for sequential sampling duri
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9407020
Autor:
Lewis, David D.1 lewis@research.att.com, Jones, Karen Sparck2 sparck-jones@cl.cam.ac.uk
Publikováno v:
Communications of the ACM. Jan1996, Vol. 39 Issue 1, p92-101. 10p.
Autor:
Cohen, Edith ††E-mail:edith,lewis@research.att.com., Lewis, David D †
Publikováno v:
In Journal of Algorithms February 1999 30(2):211-252