Zobrazeno 1 - 10
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pro vyhledávání: '"Judita Preiss"'
Autor:
Judita Preiss
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss S2, Pp 1-8 (2024)
Abstract Background Traditional literature based discovery is based on connecting knowledge pairs extracted from separate publications via a common mid point to derive previously unseen knowledge pairs. To avoid the over generation often associated w
Externí odkaz:
https://doaj.org/article/16a7467b0b634502a582b729cf5c75c2
Autor:
Judita Preiss
Publikováno v:
BMC Bioinformatics, Vol 23, Iss S9, Pp 1-10 (2023)
Abstract Background Automatic literature based discovery attempts to uncover new knowledge by connecting existing facts: information extracted from existing publications in the form of $$A \rightarrow B$$ A → B and $$B \rightarrow C$$ B → C relat
Externí odkaz:
https://doaj.org/article/fa68fdc89c9e4bc98efd49c0567dfefc
Autor:
Judita Preiss
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S10, Pp 75-80 (2019)
Abstract Background The quantity of documents being published requires researchers to specialize to a narrower field, meaning that inferable connections between publications (particularly from different domains) can be missed. This has given rise to
Externí odkaz:
https://doaj.org/article/58618d737e5641a3892fd8f544b67620
Autor:
Judita Preiss, Mark Stevenson
Publikováno v:
BMC Bioinformatics, Vol 18, Iss S7, Pp 59-67 (2017)
Abstract Background Literature based discovery (LBD) automatically infers missed connections between concepts in literature. It is often assumed that LBD generates more information than can be reasonably examined. Methods We present a detailed analys
Externí odkaz:
https://doaj.org/article/77be40c1d51a409ca2d0bb87f0f2483d
Autor:
Ahmet Aker, Radu Ion, Nikos Mastropavlos, Monica Paramita, Mārcis Pinnis, Dan Ştefănescu, Fangzhong Su, Gregor Thurmair, Elena Irimia, Nikola Ljubešić, Evangelos Kanoulas, Judita Preiss, Rob Gaizauskas, Paul Clough, Emma Barker, Nikos Glaros, Tiberiu Boroș, Inguna Skadiņa, Andrejs Vasiļjevs
Publikováno v:
Using Comparable Corpora for Under-Resourced Areas of Machine Translation ISBN: 9783319990033
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::632e700d6218a6680a0118a0751bf630
https://doi.org/10.1007/978-3-319-99004-0_8
https://doi.org/10.1007/978-3-319-99004-0_8
Autor:
Radu Ion, Ahmet Aker, Nikos Mastropavlos, Dan Tufiș, Robert Gaizauskas, Judita Preiss, Paul Clough, Alexandru Ceausu, Dan Ștefănescu, Olga Yannoutsou, Nikos Glaros, Monica Lestari Paramita
Publikováno v:
Using Comparable Corpora for Under-Resourced Areas of Machine Translation ISBN: 9783319990033
Using Comparable Corpora for Under-Resourced Areas of Machine Translation
Using Comparable Corpora for Under-Resourced Areas of Machine Translation
The availability of parallel corpora is limited, especially for under-resourced languages and narrow domains. On the other hand, the number of comparable documents in these areas that are freely available on the Web is continuously increasing. Algori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb5db40df308922cbcda42a336c7192e
https://doi.org/10.1007/978-3-319-99004-0_3
https://doi.org/10.1007/978-3-319-99004-0_3
Autor:
Zakrea Almansouri, Judita Preiss
Publikováno v:
Meta Gene. 27:100819
Objective\ud To investigate the usefulness of predicting the presence of a genetic mutation in a population based on data arising from physical examinations and its use as a validator of grading schemes.\ud \ud Methods\ud We employ an inference algor
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3d6ba672091d4770c2cf29f814fe580
https://usir.salford.ac.uk/id/eprint/58770/1/ocv002.pdf
https://usir.salford.ac.uk/id/eprint/58770/1/ocv002.pdf
Autor:
Judita Preiss
Publikováno v:
Natural Language Engineering. 12:209-228
We compare the word sense disambiguation systems submitted for the English-all-words task in SENSEVAL-2. We give several performance measures for the systems, and analyze correlations between system performance and word features. A decision tree lear
Autor:
Mark Stevenson, Judita Preiss
Publikováno v:
Computer Speech & Language. 18:201-207