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Plaintext Wikipedia dump 2018
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Rosa, Rudolf. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2018
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日本語Wikipediaを用いた慣用句の構成性の数値化
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In: https://pj.ninjal.ac.jp/corpus_center/lrw2018.html (2018)
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Predicting wikipedia infobox type information using word embeddings on categories ...
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Wikiprovenance: Are There Enough References To Every (Known) Fact On Wikidata? ...
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Wikiprovenance: Are There Enough References To Every (Known) Fact On Wikidata? ...
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The_Tower_of_Babel.jpg: Diversity of Visual Encyclopedic Knowledge Across Wikipedia Language Editions
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In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 12 No. 1 (2018): Twelfth International AAAI Conference on Web and Social Media ; 2334-0770 ; 2162-3449 (2018)
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The Evolution of the Concept of Semantic Web in the Context of Wikipedia: An Exploratory Approach to Study the Collective Conceptualization in a Digital Collaborative Environment
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In: Publications ; Volume 6 ; Issue 4 (2018)
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C-HTS: A Concept-based Hierarchical Text Segmentation Approach ; Language Resources and Evaluation Conference, LREC 2018
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Wikipromotion?: The use of Wikipedia to spread the World Cultural Heritage in Spain
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Wikipedia infobox type prediction using embeddings
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In: ISSN: 1613-0073 (2018)
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Predicting wikipedia infobox type information using word embeddings on categories
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In: ISSN: 1613-0073 (2018)
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Building effective representations for domain adaptation in coreference resolution
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Abstract:
Over the past few years, research in coreference resolution, one of the core tasks in Natural Language processing, has displayed significant improvement. However, the field of domain adaptation in coreference resolution is yet to be explored; Moosavi and Strube [2017] have shown that the performance of state-of-the-art coreference resolution systems drop when the systems are tested on datasets from different domains. We modify e2e-coref [Lee et al., 2017], a state-of-the-art coreference resolution system, to perform well on new domains by adding sparse linguistic features, incorporating information from Wikipedia, and implementing a domain adversarial network to the system. Our experiments show that each modification improves the precision of the system. We train the model on CoNLL-2012 datasets and test it on several datasets: WikiCoref, the pt documents, and the wb documents from CoNLL-2012. Our best results gains 0.50, 0.52, and 1.14 F1 improvements over the baselines of the respective test sets. ; Computer Sciences
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Keyword:
Coreference resolution; Domain adaptation; Domain adversarial; Information extraction; Natural language processing; Neural network; Wikipedia
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URL: http://hdl.handle.net/2152/68211 https://doi.org/10.15781/T2NP1X34P
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Using Wikipedia as a classroom tool — a translation experience
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Análise de textos enciclopédicos da Simple English Wikipedia e da Wikipedia: algumas discussões para o ensino de língua inglesa
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In: Revista de Estudos da Linguagem, Vol 26, Iss 2, Pp 769-792 (2018) (2018)
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A Distant Learning Approach for Extracting Hypernym Relations from Wikipedia Disambiguation Pages
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In: Procedia Computer Science - Vol. 112 - 2017 ; 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2017) ; https://hal.archives-ouvertes.fr/hal-01919073 ; 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2017), Sep 2017, Marseille, France. pp.1764-1773 (2017)
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ИСКАЖЕНИЕ ЗНАЧЕНИЙ И СМЫСЛОВ ПОЛИТИКО-ИСТОРИЧЕСКИХ СОБЫТИЙ В РАЗНОЯЗЫЧНЫХ ВЕРСИЯХ СТАТЕЙ ВИКИПЕДИИ
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Variations de la confiance et de la réputation de Wikipédia chez les jeunes (11-25 ans)
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In: https://hal-univ-tlse3.archives-ouvertes.fr/hal-03636787 ; 2017 (2017)
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ASRextractor: A Tool extracting Semantic Relations between Arabic Named Entities
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In: 3rd International Conference on Arabic Computational Linguistics (ACLing 2017) ; https://hal-univ-tours.archives-ouvertes.fr/hal-01632858 ; 3rd International Conference on Arabic Computational Linguistics (ACLing 2017), Nov 2017, Dubai, United Arab Emirates ; http://acling2017.org/ (2017)
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