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Titlebook: Semantics, Analytics, Visualization; 3rd International Wo Alejandra González-Beltrán,Francesco Osborne,Sahar Conference proceedings 2018 Sp

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發(fā)表于 2025-3-21 18:27:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Semantics, Analytics, Visualization
副標(biāo)題3rd International Wo
編輯Alejandra González-Beltrán,Francesco Osborne,Sahar
視頻videohttp://file.papertrans.cn/865/864753/864753.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Semantics, Analytics, Visualization; 3rd International Wo Alejandra González-Beltrán,Francesco Osborne,Sahar Conference proceedings 2018 Sp
描述This book constitutes the refereed proceedings of the 3.rd. International Workshop, SAVE-SD 2017, held in Perth, Australia, in April 2017, and the 4.th. International Workshop, SAVE-SD 2018, held in Lyon, France, in April 2018.?The 6 full, 2 position and 4 short papers were selected from 16 submissions. The papers describe multiple ways in which scholarly dissemination can be approved: Creating structured data, providing methods for semantic computational analysis and designing systems for navigating. This allows a variety of stakeholders to understand research dynamics, predict trends and evaluate the quality of research.
出版日期Conference proceedings 2018
關(guān)鍵詞artificial intelligence; cloud services; databases; digital libraries; grid computing; Human-Computer Int
版次1
doihttps://doi.org/10.1007/978-3-030-01379-0
isbn_softcover978-3-030-01378-3
isbn_ebook978-3-030-01379-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Optimized Machine Learning Methods Predict Discourse Segment Type in Biological Research Articles,with a reduced set of target classes. Using only verb tense features, logistic regression, a decision tree classifier and a random forest classifier, we predicted that a segment type was either a Result/Method or a Fact/Implication, with F1 scores above 0.8. Interestingly, findings from this machine
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OSCAR: A Customisable Tool for Free-Text Search over SPARQL Endpoints, data, . those provided by OpenCitations, ScholarlyData and Wikidata. We conclude by discussing the results of a user testing session that reveal the usability of the OSCAR search interface when employed to access information within the OpenCitations Corpus.
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