標題: Titlebook: Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy; 7th China Conference Maosong Sun,Guilin Qi,Yubo Chen [打印本頁] 作者: aggression 時間: 2025-3-21 17:12
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy影響因子(影響力)
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy影響因子(影響力)學科排名
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書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy網(wǎng)絡(luò)公開度學科排名
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy被引頻次
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy被引頻次學科排名
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy年度引用
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy年度引用學科排名
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy讀者反饋
書目名稱Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy讀者反饋學科排名
作者: 付出 時間: 2025-3-21 22:08
Incorporating Uncertainty of?Entities and?Relations into?Few-Shot Uncertain Knowledge Graph Embeddininty information, or require sufficient training data for each relation, we propose a novel method by incorporating the inherent uncertainty of entities and relations (i.e. element-level uncertainty) into uncertain knowledge graph embedding. We introduce different metrics to quantify the uncertainty作者: Contracture 時間: 2025-3-22 03:13
TraConcept: Constructing a?Concept Framework from?Chinese Traffic Legal Textsup first. This framework usually comprises domain-specific inter-related concepts, their relations, and their attributes, to achieve a comprehensive understanding of the subject domain. While some of the topics in the task of concept framework construction had been studied, such as the identificatio作者: 有助于 時間: 2025-3-22 07:07
Document-Level Relation Extraction with?a?Dependency Syntax Transformer and?Supervised Contrastive Lhe document level. Studies have shown that the Transformer architecture models long-distance dependencies without regard to the syntax-level dependencies between tokens in the sequence, which hinders its ability to model long-range dependencies. Furthermore, the global information among relational t作者: 要控制 時間: 2025-3-22 11:10 作者: 生意行為 時間: 2025-3-22 13:30
and so an- regend und fruchtbar gewirkt," das Unendliche ist aber auch wie kein anderer Begriff so der Aufkl?rung bedürftig. HILBERT [226, p. 163] Etwas mehr als 100 Jahre sind vergangen, seit in den Mathemati- schen Annalen der sechste und letzte Teil von CANTORS fundamenta- ler Arbeit über unendli作者: Fulminate 時間: 2025-3-22 17:20
Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy7th China Conference作者: 暫停,間歇 時間: 2025-3-22 23:36 作者: 修飾 時間: 2025-3-23 03:08
Ende des vorigen Jahrhunderts zunehmend anerkannt und verwendet, durch die Ent- deckung der Antinomien erneut erschüttert, ist die Mengenlehre in ihrer heutigen axiomatisierten Gestalt eines der Fundamente der Mathematik. Die Tatsache, da? alle mathematischen Begriffe auf mengentheoretische Begriff作者: perimenopause 時間: 2025-3-23 05:57 作者: 過分自信 時間: 2025-3-23 09:54
Document-Level Relation Extraction with?a?Dependency Syntax Transformer and?Supervised Contrastive Live learning with fusion knowledge captures global information among relational triples. Gaussian probability distributions are also designed to capture local information around entities. Our experiments on two document-level relation extraction datasets, CDR and GDA, have remarkable results.作者: surmount 時間: 2025-3-23 14:14 作者: cocoon 時間: 2025-3-23 22:05
Incorporating Uncertainty of?Entities and?Relations into?Few-Shot Uncertain Knowledge Graph Embeddinion of entities and relations in the few-shot scenario. Experimental results show that our proposed method can learn better embeddings in terms of the higher accuracy in both confidence score prediction and tail entity prediction.作者: 套索 時間: 2025-3-24 00:22 作者: narcissism 時間: 2025-3-24 02:50
KGSG: Knowledge Guided Syntactic Graph Model for Drug-Drug Interaction Extractionatical relation. We conducted comparative experiments and ablation studies on the DDI extraction 2013 dataset. The experimental results show that our method can effectively integrate domain knowledge and syntactic information to improve the performance of DDI extraction compared with the existing methods.作者: 止痛藥 時間: 2025-3-24 07:03
Conference proceedings 2022n and knowledge base construction; linked data, knowledge integration, and knowledge graph storage managements; natural language understanding and semantic computing; knowledge graph applications; and knowledge graph open resources..作者: inscribe 時間: 2025-3-24 14:27 作者: 膠狀 時間: 2025-3-24 15:10 作者: 字的誤用 時間: 2025-3-24 19:48
https://doi.org/10.1007/978-981-19-7596-7artificial intelligence; semantics; natural language processing; natural languages; information retrieva作者: Migratory 時間: 2025-3-25 00:23 作者: needle 時間: 2025-3-25 05:53
Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy978-981-19-7596-7Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 東西 時間: 2025-3-25 10:03
Communications in Computer and Information Sciencehttp://image.papertrans.cn/k/image/543933.jpg作者: 粉筆 時間: 2025-3-25 14:52
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