Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Matthias Irmer"'
Autor:
Matthias Irmer
This book presents work on bridging inferences in discourse interpretation. It develops a formalization that permits integrating indirect anaphora in the construction of a structured discourse representation. From a broader perspective, it provides a
Autor:
Shadrack J. Barnabas, Timo Böhme, Stephen K. Boyer, Matthias Irmer, Christoph Ruttkies, Ian Wetherbee, Todor Kondić, Emma L. Schymanski, Lutz Weber
Publikováno v:
Digital Discovery. 1:490-501
Extracting PFAS with open source cheminformatics toolkits reveals ~1.78 million PFAS in Google Patents, ~28 K in the CORE literature repository. The extraction of chemical information from documents is a demanding task in cheminformatics due to the v
Autor:
Matthias Irmer
Publikováno v:
Towards a Vigilant Society ISBN: 9780197267080
Bridging Inferences: Constraining and Resolving Underspecification in Discourse Interpretation
Bridging Inferences: Constraining and Resolving Underspecification in Discourse Interpretation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b606eb924ce20ca13872e131e3c3447
https://doi.org/10.5871/bacad/9780197267080.002.0006
https://doi.org/10.5871/bacad/9780197267080.002.0006
Autor:
Shadrack Barnabas, Timo Böhme, Stephen Boyer, Matthias Irmer, Christoph Ruttkies, Todor Kondic, Emma Schymanski, Lutz Weber
The extraction of chemical information from documents is a demanding task in cheminformatics due to the variety of text and image-based representations of chemistry. The present work describes the extraction of chemical compounds with unique chemical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e24be66a7ecbfae70fd18e3fa5423a5
https://doi.org/10.26434/chemrxiv-2022-nmnnd
https://doi.org/10.26434/chemrxiv-2022-nmnnd
Autor:
Olav Mueller-Reichau, Matthias Irmer
Publikováno v:
Journal of Semantics.
Autor:
Matthias Irmer
Publikováno v:
Lingua. 132:29-50
Two types of implicit meaning aspects play an important role in discourses comprising more than one utterance: implicatures that arise when the linguistic input is minimized, and inferences that establish connections between utterances in order to fo
Autor:
Thaer M. Dieb, Matthias Irmer, Buzhou Tang, Shuo Xu, Yanan Lu, Rafal Rak, Madian Khabsa, Caglar Ata, Isabel Segura-Bedmar, Riza Theresa Batista-Navarro, Donghong Ji, Lutz Weber, Tim Rocktäschel, Hong-Jie Dai, Daniel M. Lowe, Miguel Vazquez, Roger A. Sayle, Hongfang Liu, Saber A. Akhondi, Martin Krallinger, Paloma Martínez, Marko Bajec, Keun Ho Ryu, Julen Oyarzabal, Zhiyong Lu, Torsten Huber, Karin Verspoor, Richard Tzong-Han Tsai, Masaharu Yoshioka, Rui Alves, Slavko Žitnik, David Campos, Florian Leitner, Asif Ekbal, David Salgado, Miji Choi, Obdulia Rabal, Andre Lamurias, Senthil Nathan, Robert Leaman, Anabel Usié, Hua Xu, S. V. Ramanan, Sérgio Matos, Tsendsuren Munkhdalai, Tolga Can, Utpal Kumar Sikdar, Jan A. Kors, C. Lee Giles, Alfonso Valencia, Francisco M. Couto, Komandur Elayavilli Ravikumar, Xin An
Publikováno v:
Journal of Cheminformatics, ISSN 1758-2946, 2015, Vol. 7, No. 1
Repositorio Abierto de la UdL
Universitad de Lleida
Journal of Cheminformatics
Recercat. Dipósit de la Recerca de Catalunya
instname
Journal of Cheminformatics, 7(suppl):S2. Chemistry Central
Dadun. Depósito Académico Digital de la Universidad de Navarra
Archivo Digital UPM
Universidad Politécnica de Madrid
Repositorio Abierto de la UdL
Universitad de Lleida
Journal of Cheminformatics
Recercat. Dipósit de la Recerca de Catalunya
instname
Journal of Cheminformatics, 7(suppl):S2. Chemistry Central
Dadun. Depósito Académico Digital de la Universidad de Navarra
Archivo Digital UPM
Universidad Politécnica de Madrid
The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4706ccb2aeaf76c0f9cfebc9318cbb8f
https://oa.upm.es/41177/
https://oa.upm.es/41177/
Publikováno v:
Pharmaceutical patent analyst. 2(1)
Ontology-based semantic text analysis methods allow to automatically extract knowledge relationships and data from text documents. In this review, we have applied these technologies for the systematic analysis of pharmaceutical patents. Hierarchical