Clientele
发表于 2025-3-21 19:39:47
书目名称Analysis of Images, Social Networks and Texts影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0156381<br><br> <br><br>书目名称Analysis of Images, Social Networks and Texts读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0156381<br><br> <br><br>
刺耳
发表于 2025-3-21 21:37:56
Unsupervised Ultra-Fine Entity Typing with Distributionally Induced Word Sensesr for a mention. Experimental results on an ultra-fine entity typing task demonstrate that combining our predictions with the predictions of an existing neural model leads to a slight improvement over the ultra-fine types for mentions that are not pronouns.
CRUC
发表于 2025-3-22 02:19:30
0302-9743 data analysis and machine learning; network analysis; and theoretical machine learning and optimization. The book also contains one invited talk in full paper length. .978-3-031-54533-7978-3-031-54534-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
Scintillations
发表于 2025-3-22 06:21:48
0302-9743 mages, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023. .The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: natural language processing; computer vision;
Missile
发表于 2025-3-22 11:21:43
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gastritis
发表于 2025-3-22 12:54:58
Alan Brown,Jerry Fishenden,Mark Thompsonges through semantic shifts in the News and Social media corpora; the latter was collected and released as a part of this work. In addition, we compare the performance of these three approaches and highlight their strengths and weaknesses for this task.
违抗
发表于 2025-3-22 19:32:39
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magnate
发表于 2025-3-22 22:16:32
Static, Dynamic, or Contextualized: What is the Best Approach for Discovering Semantic Shifts in Rusges through semantic shifts in the News and Social media corpora; the latter was collected and released as a part of this work. In addition, we compare the performance of these three approaches and highlight their strengths and weaknesses for this task.
心神不宁
发表于 2025-3-23 04:14:19
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剧毒
发表于 2025-3-23 09:32:38
RuCAM: Comparative Argumentative Machine for the Russian Languagen with respect to information extracted from the OSCAR corpus. We also introduce several datasets for the RuCAM subtasks: comparative question classification, object and aspect identification, comparative sentences classification. We provide models for each subtask and compare them with the existing baselines.