Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

NAVEGAR
EXPORTAR
- Exportar todas as publicações
- Export author
ORDENAR POR
- Autor
- Título
- Tipo/journal
- Ano
- Mais recente
SITE
- Ajuda
- Sobre esse site
USUÁRIO GUEST
Guest
ENTRE
Nome:

Senha:

Deutsch, English, Nederlands, Norsk, Português, <mais...>

Primeiro nome(s):	S.
Sobrenome(s):	Ananiadou

| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-389 |

Bannach-Brown, A., Przybyɫa, P., Thomas, J., Rice, A., Ananiadou, S., Liao, J. and Macleod, M. R., Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error (2019), in: Systematic Reviews, 8(23)

[DOI]
[URL]

Mo, Y., Kontonatsios, G. and Ananiadou, S., Supporting Systematic Reviews Using LDA-based Document Representations (2015), in: Systematic Reviews, 4(172)

[DOI]
[URL]

O'Mara-Eves, A., Thomas, J., McNaught, J., Miwa, M. and Ananiadou, S., Using text mining for study identification in systematic reviews: A systematic review of current approaches (2015), in: Systematic Reviews, 4:1

[DOI]
[URL]

Thompson, P. and Ananiadou, S., HYPHEN: A flexible, hybrid method to map phenotype concept mentions to terminological resources (2018), in: Terminology, 24:1(91-121)

[DOI]
[URL]

Piao, S., Tsuruoka, Y. and Ananiadou, S., Sentiment Analysis with Knowledge Resource and NLP Tools (2009), in: The International Journal of Interdisciplinary Social Sciences, 4:5(17--28)

[URL]

Sousselier, L., Roncaglioni, A., Raitano, G., Petoumenou, M., Benfenati, E., Ananiadou, S., Nguyen, N. T. H., Do, Q. T., Paya, E., Olivier, E., Wakx, A., Michel, S., Dufat, H. and Rat, P., Role of in silico tools and text mining in the risk assessment of selected alkaloids (2018), in: Toxicology Letters, 295:Supplement 1(S159)

[URL]

Raitano, G., Benfenati, E., Ananiadou, S., Nguyen, N. T. H., Do, Q. T., Rat, P. and Sousselier, L., Role of in silico tools and text mining in the safety assessment of selected plant coumarins (2017), in: Toxicology Letters, 280:Supplement 1(S96)

[DOI]
[URL]

Brockmeier, A. J., Mu, T., Ananiadou, S. and Goulermas, J. Y, Self-Tuned Descriptive Document Clustering using a Predictive Network (2018), in: Transactions on Knowledge and Data Engineering

[URL]

Ananiadou, S., Pyysalo, S., Tsujii, J. and Kell, D. B., Event extraction for systems biology by text mining the literature (2010), in: Trends in Biotechnology, 28:7(381-390)

[DOI]

Ananiadou, S., Kell, D. B. and Tsujii, J., Text mining and its potential applications in systems biology (2006), in: Trends in Biotechnology, 24:12(571 - 579)

attachment

Leroi, A. M., Lambert, B. C., Mauch, M., Papadopoulou, M., Ananiadou, S., Lindberg, S. I. I. and Lindenfors, P., On Revolutions (2018), in: V-Dem Working Paper(63)

[DOI]
[URL]

Venkatesan, A., Kim, J. -H., Talo, F., Ide-Smith, M., Gobeill, J., Carter, J., Batista-Navarro, R., Ananiadou, S., Ruch, P. and McEntyre, J. R., SciLite: a platform for displaying text-mined annotations as a means to link research articles with biological data [version 2; referees: 2 approved, 1 approved with reservations]. (2017), in: Wellcome Open Res, 1:25

[DOI]
[URL]

EntitÃ©s NommÃ©es, ATALA, Traitement Automatique des Langues, volume 54, 2013

[URL]

Text Mining for Biology And Biomedicine, Artech House, Inc., 2006

[URL]

Batista-Navarro, R., Zerva, C., Nguyen, N. T. H. and Ananiadou, S., A Text Mining-Based Framework for Constructing an RDF-Compliant Biodiversity Knowledge Repository, páginas 30-42, Springer, Communications in Computer and Information Science, volume 656, 2017

[DOI]
[URL]

Inan, E., Thompson, P., Christopoulou, F., Yates, T. and Ananiadou, S., Knowledge Graph Enrichment of a Semantic Search System for Construction Safety, in: Intelligent Systems and Applications. IntelliSys 2022., páginas 33-52, Springer, Cham, 2022

[DOI]
[URL]

Ananiadou, S. and Thompson, P., Supporting Biological Pathway Curation Through Text Mining, in: Data Analytics and Management in Data Intensive Domains, páginas 59-73, Springer, 2017

[DOI]
[URL]

Thompson, P., Ananiadou, S. and Tsujii, J., The GENIA Corpus: Annotation Levels and Applications, in: Handbook of Linguistic Annotation, páginas 1395-1432, Springer, 2017

[DOI]
[URL]

Black, W.J., Rowley, A., Miwa, M., McNaught, J. and Ananiadou, S., Text Mining for Semantic Search in Europe PubMed Central Labs, in: Working with Text: Tools, Techniques and Approaches for Text Mining, páginas 111-132, Elsevier, 2016

[URL]

MihÄƒilÄƒ, C., Batista-Navarro, R., Alnazzawi, N., Kontonatsios, G., Korkontzelos, I., Rak, R., Thompson, P. and Ananiadou, S., Mining the biomedical literature, in: Healthcare Data Analytics, páginas 251-308, CRC Press, 2015

[URL]

Kontonatsios, G., MihÄƒilÄƒ, C., Korkontzelos, I., Thompson, P. and Ananiadou, S., A hybrid approach to compiling bilingual dictionaries of medical terms from parallel corpora, in: Statistical Language and Speech Processing, Second International Conference, SLSP 2014, páginas 57-69, Springer, 2014

[DOI]

Rosner, M., Attard, A., Thompson, P., Gatt, A. and Ananiadou, S., Extending a Tool Resource Framework with U-Compare, in: Human Language Technology Challenges for Computer Science and Linguistics, páginas 315-326, Springer, 2014

[URL]

Ananiadou, S., Thompson, P. and Nawaz, R., Enhancing Search: Events and their Discourse Context, in: Computational Linguistics and Intelligent Text Processing, páginas 318-334, Springer, 2013

[DOI]
[URL]

Batista-Navarro, R., Kontonatsios, G., MihÄƒilÄƒ, C., Thompson, P., Rak, R., Nawaz, R., Korkontzelos, I. and Ananiadou, S., Facilitating the Analysis of Discourse Phenomena in an Interoperable NLP Platform, in: Computational Linguistics and Intelligent Text Processing, páginas 559-571, Springer Berlin Heidelberg, 2013

[DOI]
[URL]

Ananiadou, S., McNaught, J. and Thompson, P., The English Language in the Digital Age, in: White Paper Series, Springer, 2012

[URL]

| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-389 |

tempo de processamento: 0.0822 segundos.