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description Publicationkeyboard_double_arrow_right Conference object 2021With the increasing adoption of technology, more and more systems become target to information security breaches. In terms of readily identifying zero-day vulnerabilities, a substantial number of news outlets and social media accounts reveal emerging vulnerabilities and threats. However, analysts often spend a lot of time looking through these decentralized sources of information in order to ensure up-to-date countermeasures and patches applicable to their organisation’s information systems. Various automated processing pipelines grounded in Natural Language Processing techniques for text classification were introduced for the early identification of vulnerabilities starting from Open-Source Intelligence (OSINT) data, including news websites, blogs, and social media. In this study, we consider a corpus of more than 1600 labeled news articles, and introduce an interpretable approach to the subject of cyberthreat early detection. In particular, an interpretable classification is performed using the Longformer architecture alongside prototypes from the ProSeNet structure, after performing a preliminary analysis on the Transformer’s encoding capabilities. The best interpretable architecture achieves an 88% F2-Score, arguing for the system’s applicability in real-life monitoring conditions of OSINT data.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.26615/978-954-452-072-4_049&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.26615/978-954-452-072-4_049&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2020 United KingdomPublisher:International Committee on Computational Linguistics Funded by:EC | M and MEC| M and MAuthors: Mitchell, Jeffrey J; Bowers, Jeffrey S;Mitchell, Jeffrey J; Bowers, Jeffrey S;Recently, domain-general recurrent neural networks, without explicit linguistic inductive biases, have been shown to successfully reproduce a range of human language behaviours, such as accurately predicting number agreement between nouns and verbs. We show that such networks will also learn number agreement within unnatural sentence structures, i.e. structures that are not found within any natural languages and which humans struggle to process. These results suggest that the models are learning from their input in a manner that is substantially different from human language acquisition, and we undertake an analysis of how the learned knowledge is stored in the weights of the network. We find that while the model has an effective understanding of singular versus plural for individual sentences, there is a lack of a unified concept of number agreement connecting these processes across the full range of inputs. Moreover, the weights handling natural and unnatural structures overlap substantially, in a way that underlines the non-human-like nature of the knowledge learned by the network.
Explore Bristol Rese... arrow_drop_down Explore Bristol Research; OpenAIREContribution for newspaper or weekly magazine . Conference object . 2020https://doi.org/10.18653/v1/20...Other literature type . Conference object . 2020 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/2020.coling-main.451&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 5 citations 5 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Explore Bristol Rese... arrow_drop_down Explore Bristol Research; OpenAIREContribution for newspaper or weekly magazine . Conference object . 2020https://doi.org/10.18653/v1/20...Other literature type . Conference object . 2020 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/2020.coling-main.451&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type , Part of book or chapter of book 2020Publisher:Springer International Publishing Funded by:EC | IASISEC| IASISAuthors: Oswaldo Solarte-Pabon; Ernestina Menasalvas; Alejandro Rodríguez-González;Oswaldo Solarte-Pabon; Ernestina Menasalvas; Alejandro Rodríguez-González;Electronic health records contain valuable information written in narrative form. A relevant challenge in clinical narrative text is that concepts commonly appear negated. Several proposals have been developed to detect negation in clinical text written in Spanish. Much of these proposals have adapted the Negex algorithm to Spanish, but obtained results indicating lower performance than NegEx implementations in other languages. Moreover, in most of these proposals, the validation process could be improved using a shared test corpus focused on negation in clinical text. This paper proposes Spa-neg, an approach to improve negation detection in clinical text written in Spanish. Spa-neg combines three elements: (i) an exploratory data analysis of how negation is written in the clinical text, (ii) use of regular expressions best adapted to the way in which negation is expressed in Spanish, (iii) experiments, and validation using a shared annotated corpus focused on negation. Our findings suggest that the combination of these elements improves the process of negation detection. The tests performed have shown 92% F-Score using IULA Spanish, an annotated corpus for negation in clinical text.
ZENODO arrow_drop_down https://doi.org/10.1007/978-3-...Part of book or chapter of book . 2020 . Peer-reviewedLicense: Springer TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-030-45385-5_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Average influence Average impulse Average Powered by BIP!visibility 160visibility views 160 download downloads 164 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.1007/978-3-...Part of book or chapter of book . 2020 . Peer-reviewedLicense: Springer TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-030-45385-5_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publication2019 EnglishPublisher:Cognitive Computational Neuroscience Funded by:EC | M and MEC| M and MAuthors: Blything, Ryan; Vankov, Ivan; Ludwig, Casimir; Bowers, Jeffrey;Blything, Ryan; Vankov, Ivan; Ludwig, Casimir; Bowers, Jeffrey;OpenAIRE arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.32470/ccn.2019.1091-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert OpenAIRE arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.32470/ccn.2019.1091-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2019 Portugal EnglishAuthors: Sousa, Alexandre; Ribeiro, Cláudio;Sousa, Alexandre; Ribeiro, Cláudio;handle: 10316/100259
As the growing possibilities for disseminating digital objects of cultural heritage on the Internet, some institutions dealing with documents and objects, identified from this spectrum, have encountered certain difficulties in measuring the best forms of organization and dissemination of information on the web, which currently extrapolate the traditional collection and listing of data from libraries, archives and museum catalogs. Semantic Web technologies and Linked Data principles have been pointed out as a facilitator for the structuring and interconnection between collections from different backgrounds, through the use of some guidelines for publication and data relationship. This can meet the longing for memory institutions in organizing the information of their digital objects on a particular theme. There are already initiatives for the publication of open data interlinked cultural heritage, such as the Europeana Library, which uses the Europeana Data Model (EDM) to relate and curate cultural data between collections of European institutions. The possibility of working biographical aspects between digital objects of documentary resources, through the EDM description and the (re) use of vocabularies already developed in Linked Data, to extend the semantics of the described objects, is the objective of this work. For that, a case study, restricted and illustrative, not exhaustive, will be made with documents on the scientist Oswaldo Cruz, pioneer in the study of infectious and parasitic diseases and experimental medicine in Brazil. Based on objects collected in the collections collected by the Oswaldo Cruz Foundation (FIOCRUZ), on the memory of the life and work of the patron of the institution, the selected examples were representation using the EDM and the possibilities of linking the biographical aspects between the resources were explored through the use of established vocabularies. Thus it was possible to verify and analyze how the Linked Data principles can extend the semantics of the data, linking objects thematically, thus gaining a chance to be explored in the internet by original forms of discovery and reuse.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10316/100259&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10316/100259&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Presentation 2019Publisher:Figshare Authors: Demeranville, Tom; Olson, Eric; Minihan, Brian;Demeranville, Tom; Olson, Eric; Minihan, Brian;"Cooking with ORCID: Understanding and Sharing ORCID Connections" was presented by Eric Olson, Brian Minihan, and Tom Demeranville at the ORCID Consortia Workshop on May 20, 2019.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23640/07243.8184356&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23640/07243.8184356&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Presentation 2018 EnglishPublisher:Zenodo Funded by:EC | POSTDATAEC| POSTDATAAuthors: Ros; Salvador;Ros; Salvador;Presentation at the EADH 2018: "Data in Digital Humanities" at National University of Ireland, Galway 7-9 December 2018
ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.2202995&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 53visibility views 53 download downloads 34 Powered bymore_vert ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.2202995&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Contribution for newspaper or weekly magazine , Other literature type 2018 France, Switzerland, United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | HimL, EC | TraMOOC +2 projectsEC| SUMMA ,EC| HimL ,EC| TraMOOC ,SNSF| Rich Context in Neural Machine Translation ,SNSF| Dating structural fabric development using high spatial resolution 40Ar/39Ar geochronology: a Combined Filed and Experimental ApproachAuthors: Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, designed to test the models' ability to exploit previous source and target sentences. We investigate the performance of recently proposed multi-encoder NMT models trained on subtitles for English to French. We also explore a novel way of exploiting context from the previous sentence. Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50% accuracy on our coreference test set and 53.5% for coherence/cohesion (compared to a non-contextual baseline of 50%). A simple strategy of decoding the concatenation of the previous and current sentence leads to good performance, and our novel strategy of multi-encoding and decoding of two sentences leads to the best performance (72.5% for coreference and 57% for coherence/cohesion), highlighting the importance of target-side context. Comment: Final version of paper to appear in Proceedings of NAACL 2018
OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 89 citations 89 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2017 PortugalPublisher:ACM Authors: Freitas, Cristiana; Borges, Maria Manuel; Revez, Jorge;Freitas, Cristiana; Borges, Maria Manuel; Revez, Jorge;handle: 10316/45733 , 10451/30062
The availability of digitised cultural heritage content held by archives and other memory institutions improves their visibility, facilitate and increases access to information, allowing new kinds of research of digital heritage, namely Digital Humanities. This study intends to report how Municipal Archives of mainland Portugal are ensuring access to their digitized cultural heritage content. For this purpose, an analysis was held to collect data about online catalogues with digital objects linked to the archival description in 278 Municipal Archives of mainland Portugal. The data revealed that the openness of the primary information sources preserved by the municipal archives, which can be reused by all those who need them and particularly by digital humanists, is still in infancy.
E-LIS arrow_drop_down Universidade de Lisboa: Repositório.ULConference object . 2017Data sources: Universidade de Lisboa: Repositório.ULhttps://doi.org/10.1145/314482...Conference object . 2017 . Peer-reviewedLicense: ACM Copyright PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3144826.3145383&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert E-LIS arrow_drop_down Universidade de Lisboa: Repositório.ULConference object . 2017Data sources: Universidade de Lisboa: Repositório.ULhttps://doi.org/10.1145/314482...Conference object . 2017 . Peer-reviewedLicense: ACM Copyright PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3144826.3145383&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2017 United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | ENCASEEC| ENCASEJoan Serra; Ilias Leontiadis; Dimitris Spathis; Gianluca Stringhini; Jeremy Blackburn; Athena Vakali;Common approaches to text categorization essentially rely either on n-gram counts or on word embeddings. This presents important difficulties in highly dynamic or quickly-interacting environments, where the appearance of new words and/or varied misspellings is the norm. A paradigmatic example of this situation is abusive online behavior, with social networks and media platforms struggling to effectively combat uncommon or nonblacklisted hate words. To better deal with these issues in those fast-paced environments, we propose using the error signal of class-based language models as input to text classification algorithms. In particular, we train a next-character prediction model for any given class, and then exploit the error of such class-based models to inform a neural network classifier. This way, we shift from the ability to describe seen documents to the ability to predict unseen content. Preliminary studies using out-of-vocabulary splits from abusive tweet data show promising results, outperforming competitive text categorization strategies by 4–11%
https://www.aclweb.o... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/w17-3005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 20 citations 20 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!visibility 69visibility views 69 download downloads 52 Powered bymore_vert https://www.aclweb.o... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/w17-3005&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Conference object 2021With the increasing adoption of technology, more and more systems become target to information security breaches. In terms of readily identifying zero-day vulnerabilities, a substantial number of news outlets and social media accounts reveal emerging vulnerabilities and threats. However, analysts often spend a lot of time looking through these decentralized sources of information in order to ensure up-to-date countermeasures and patches applicable to their organisation’s information systems. Various automated processing pipelines grounded in Natural Language Processing techniques for text classification were introduced for the early identification of vulnerabilities starting from Open-Source Intelligence (OSINT) data, including news websites, blogs, and social media. In this study, we consider a corpus of more than 1600 labeled news articles, and introduce an interpretable approach to the subject of cyberthreat early detection. In particular, an interpretable classification is performed using the Longformer architecture alongside prototypes from the ProSeNet structure, after performing a preliminary analysis on the Transformer’s encoding capabilities. The best interpretable architecture achieves an 88% F2-Score, arguing for the system’s applicability in real-life monitoring conditions of OSINT data.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.26615/978-954-452-072-4_049&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.26615/978-954-452-072-4_049&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2020 United KingdomPublisher:International Committee on Computational Linguistics Funded by:EC | M and MEC| M and MAuthors: Mitchell, Jeffrey J; Bowers, Jeffrey S;Mitchell, Jeffrey J; Bowers, Jeffrey S;Recently, domain-general recurrent neural networks, without explicit linguistic inductive biases, have been shown to successfully reproduce a range of human language behaviours, such as accurately predicting number agreement between nouns and verbs. We show that such networks will also learn number agreement within unnatural sentence structures, i.e. structures that are not found within any natural languages and which humans struggle to process. These results suggest that the models are learning from their input in a manner that is substantially different from human language acquisition, and we undertake an analysis of how the learned knowledge is stored in the weights of the network. We find that while the model has an effective understanding of singular versus plural for individual sentences, there is a lack of a unified concept of number agreement connecting these processes across the full range of inputs. Moreover, the weights handling natural and unnatural structures overlap substantially, in a way that underlines the non-human-like nature of the knowledge learned by the network.
Explore Bristol Rese... arrow_drop_down Explore Bristol Research; OpenAIREContribution for newspaper or weekly magazine . Conference object . 2020https://doi.org/10.18653/v1/20...Other literature type . Conference object . 2020 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/2020.coling-main.451&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 5 citations 5 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Explore Bristol Rese... arrow_drop_down Explore Bristol Research; OpenAIREContribution for newspaper or weekly magazine . Conference object . 2020https://doi.org/10.18653/v1/20...Other literature type . Conference object . 2020 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/2020.coling-main.451&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type , Part of book or chapter of book 2020Publisher:Springer International Publishing Funded by:EC | IASISEC| IASISAuthors: Oswaldo Solarte-Pabon; Ernestina Menasalvas; Alejandro Rodríguez-González;Oswaldo Solarte-Pabon; Ernestina Menasalvas; Alejandro Rodríguez-González;Electronic health records contain valuable information written in narrative form. A relevant challenge in clinical narrative text is that concepts commonly appear negated. Several proposals have been developed to detect negation in clinical text written in Spanish. Much of these proposals have adapted the Negex algorithm to Spanish, but obtained results indicating lower performance than NegEx implementations in other languages. Moreover, in most of these proposals, the validation process could be improved using a shared test corpus focused on negation in clinical text. This paper proposes Spa-neg, an approach to improve negation detection in clinical text written in Spanish. Spa-neg combines three elements: (i) an exploratory data analysis of how negation is written in the clinical text, (ii) use of regular expressions best adapted to the way in which negation is expressed in Spanish, (iii) experiments, and validation using a shared annotated corpus focused on negation. Our findings suggest that the combination of these elements improves the process of negation detection. The tests performed have shown 92% F-Score using IULA Spanish, an annotated corpus for negation in clinical text.
ZENODO arrow_drop_down https://doi.org/10.1007/978-3-...Part of book or chapter of book . 2020 . Peer-reviewedLicense: Springer TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-030-45385-5_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Average influence Average impulse Average Powered by BIP!visibility 160visibility views 160 download downloads 164 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.1007/978-3-...Part of book or chapter of book . 2020 . Peer-reviewedLicense: Springer TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/978-3-030-45385-5_29&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publication2019 EnglishPublisher:Cognitive Computational Neuroscience Funded by:EC | M and MEC| M and MAuthors: Blything, Ryan; Vankov, Ivan; Ludwig, Casimir; Bowers, Jeffrey;Blything, Ryan; Vankov, Ivan; Ludwig, Casimir; Bowers, Jeffrey;OpenAIRE arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.32470/ccn.2019.1091-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert OpenAIRE arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.32470/ccn.2019.1091-0&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2019 Portugal EnglishAuthors: Sousa, Alexandre; Ribeiro, Cláudio;Sousa, Alexandre; Ribeiro, Cláudio;handle: 10316/100259
As the growing possibilities for disseminating digital objects of cultural heritage on the Internet, some institutions dealing with documents and objects, identified from this spectrum, have encountered certain difficulties in measuring the best forms of organization and dissemination of information on the web, which currently extrapolate the traditional collection and listing of data from libraries, archives and museum catalogs. Semantic Web technologies and Linked Data principles have been pointed out as a facilitator for the structuring and interconnection between collections from different backgrounds, through the use of some guidelines for publication and data relationship. This can meet the longing for memory institutions in organizing the information of their digital objects on a particular theme. There are already initiatives for the publication of open data interlinked cultural heritage, such as the Europeana Library, which uses the Europeana Data Model (EDM) to relate and curate cultural data between collections of European institutions. The possibility of working biographical aspects between digital objects of documentary resources, through the EDM description and the (re) use of vocabularies already developed in Linked Data, to extend the semantics of the described objects, is the objective of this work. For that, a case study, restricted and illustrative, not exhaustive, will be made with documents on the scientist Oswaldo Cruz, pioneer in the study of infectious and parasitic diseases and experimental medicine in Brazil. Based on objects collected in the collections collected by the Oswaldo Cruz Foundation (FIOCRUZ), on the memory of the life and work of the patron of the institution, the selected examples were representation using the EDM and the possibilities of linking the biographical aspects between the resources were explored through the use of established vocabularies. Thus it was possible to verify and analyze how the Linked Data principles can extend the semantics of the data, linking objects thematically, thus gaining a chance to be explored in the internet by original forms of discovery and reuse.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10316/100259&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10316/100259&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Presentation 2019Publisher:Figshare Authors: Demeranville, Tom; Olson, Eric; Minihan, Brian;Demeranville, Tom; Olson, Eric; Minihan, Brian;"Cooking with ORCID: Understanding and Sharing ORCID Connections" was presented by Eric Olson, Brian Minihan, and Tom Demeranville at the ORCID Consortia Workshop on May 20, 2019.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23640/07243.8184356&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23640/07243.8184356&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Presentation 2018 EnglishPublisher:Zenodo Funded by:EC | POSTDATAEC| POSTDATAAuthors: Ros; Salvador;Ros; Salvador;Presentation at the EADH 2018: "Data in Digital Humanities" at National University of Ireland, Galway 7-9 December 2018
ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.2202995&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 53visibility views 53 download downloads 34 Powered bymore_vert ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.2202995&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Contribution for newspaper or weekly magazine , Other literature type 2018 France, Switzerland, United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | HimL, EC | TraMOOC +2 projectsEC| SUMMA ,EC| HimL ,EC| TraMOOC ,SNSF| Rich Context in Neural Machine Translation ,SNSF| Dating structural fabric development using high spatial resolution 40Ar/39Ar geochronology: a Combined Filed and Experimental ApproachAuthors: Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, designed to test the models' ability to exploit previous source and target sentences. We investigate the performance of recently proposed multi-encoder NMT models trained on subtitles for English to French. We also explore a novel way of exploiting context from the previous sentence. Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50% accuracy on our coreference test set and 53.5% for coherence/cohesion (compared to a non-contextual baseline of 50%). A simple strategy of decoding the concatenation of the previous and current sentence leads to good performance, and our novel strategy of multi-encoding and decoding of two sentences leads to the best performance (72.5% for coreference and 57% for coherence/cohesion), highlighting the importance of target-side context. Comment: Final version of paper to appear in Proceedings of NAACL 2018
OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 89 citations 89 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object 2017 PortugalPublisher:ACM Authors: Freitas, Cristiana; Borges, Maria Manuel; Revez, Jorge;Freitas, Cristiana; Borges, Maria Manuel; Revez, Jorge;handle: 10316/45733 , 10451/30062
The availability of digitised cultural heritage content held by archives and other memory institutions improves their visibility, facilitate and increases access to information, allowing new kinds of research of digital heritage, namely Digital Humanities. This study intends to report how Municipal Archives of mainland Portugal are ensuring access to their digitized cultural heritage content. For this purpose, an analysis was held to collect data about online catalogues with digital objects linked to the archival description in 278 Municipal Archives of mainland Portugal. The data revealed that the openness of the primary information sources preserved by the municipal archives, which can be reused by all those who need them and particularly by digital humanists, is still in infancy.
E-LIS arrow_drop_down Universidade de Lisboa: Repositório.ULConference object . 2017Data sources: Universidade de Lisboa: Repositório.ULhttps://doi.org/10.1145/314482...Conference object . 2017 . Peer-reviewedLicense: ACM Copyright PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3144826.3145383&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert E-LIS arrow_drop_down Universidade de Lisboa: Repositório.ULConference object . 2017Data sources: Universidade de Lisboa: Repositório.ULhttps://doi.org/10.1145/314482...Conference object . 2017 . Peer-reviewedLicense: ACM Copyright PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3144826.3145383&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2017 United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | ENCASEEC| ENCASEJoan Serra; Ilias Leontiadis; Dimitris Spathis; Gianluca Stringhini; Jeremy Blackburn; Athena Vakali;Common approaches to text categorization essentially rely either on n-gram counts or on word embeddings. This presents important difficulties in highly dynamic or quickly-interacting environments, where the appearance of new words and/or varied misspellings is the norm. A paradigmatic example of this situation is abusive online behavior, with social networks and media platforms struggling to effectively combat uncommon or nonblacklisted hate words. To better deal with these issues in those fast-paced environments, we propose using the error signal of class-based language models as input to text classification algorithms. In particular, we train a next-character prediction model for any given class, and then exploit the error of such class-based models to inform a neural network classifier. This way, we shift from the ability to describe seen documents to the ability to predict unseen content. Preliminary studies using out-of-vocabulary splits from abusive tweet data show promising results, outperforming competitive text categorization strategies by 4–11%
https://www.aclweb.o... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/w17-3005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 20 citations 20 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!visibility 69visibility views 69 download downloads 52 Powered bymore_vert https://www.aclweb.o... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/w17-3005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu