Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Lehnert, Wendy"'
Autor:
McCarthy, Joseph F., Lehnert, Wendy G.
This paper describes RESOLVE, a system that uses decision trees to learn how to classify coreferent phrases in the domain of business joint ventures. An experiment is presented in which the performance of RESOLVE is compared to the performance of a m
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9505043
One of the central knowledge sources of an information extraction system is a dictionary of linguistic patterns that can be used to identify the conceptual content of a text. This paper describes CRYSTAL, a system which automatically induces a dictio
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9505020
Autor:
Soderland, Stephen, Lehnert, Wendy
The availability of large on-line text corpora provides a natural and promising bridge between the worlds of natural language processing (NLP) and machine learning (ML). In recent years, the NLP community has been aggressively investigating statistic
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9406016
Autor:
Lehnert, Wendy G.
Thesis--Yale.
Includes bibliographical references (leaves 469-472).
Includes bibliographical references (leaves 469-472).
Externí odkaz:
http://catalog.hathitrust.org/api/volumes/oclc/80024244.html
Autor:
Cowie, Jim1 jcowie@nmsu.edu, Lehnert, Wendy2 lehnert@cs.umass.edu
Publikováno v:
Communications of the ACM. Jan1996, Vol. 39 Issue 1, p80-91. 12p.
Autor:
Lehnert, Wendy, Sundheim, Beth
Publikováno v:
AI Magazine; Vol 12, No 3: Fall 1991; 81
A performance evaluation of 15 text-analysis systems was recently conducted to realistically assess the state of the art for detailed information extraction from unconstrained continuous text. Reports associated with terrorism were chosen as the targ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=issn07384602::5689b2d8cd00bbc3972806c88525a72f
http://aaai.org/ojs/index.php/aimagazine/article/view/905
http://aaai.org/ojs/index.php/aimagazine/article/view/905
Autor:
Lehnert, Wendy G.
Publikováno v:
Theoretical Issues In Natural Language Processing; 1/7/1987, p80-85, 6p