Results 11 to 20 of about 554,031 (298)
Name That Graph Revealed - Oligarchy 2.0
, 2007 Web 2.0 may be all about participation, but the numbers reported by The McKinsey Quarterly suggest a self-selecting oligarchy rather than a democracy. Success may well depend more on engaging the top 2-10% of users rather than appealing to all of them. Food for though when forming your next community, be it electronic or otherwise.
Richard L. Apodaca
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Annals of Computer Science and Information Systems, 2018 The amount of information that is stored and processed by computer systems is constantly increasing. The relational model is still popular. Unfortunately, despite its simplicity, it has many disadvantages, which more often exclude it from large-scale applications.
Dominik Tomaszuk, Łukasz Szeremeta
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An Improved Approach to the Construction of Chinese Medical Knowledge Graph Based on CTD-BLSTM Model
IEEE Access, 2021 In the process of constructing the knowledge graph, entity recognition and relationship extraction are not only the most fundamental but also the most important tasks, and the effect of their model directly affects the final result of the graph.
Yang Wu, Xiyong Zhu, Yinan Zhu
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Chinese Named Entity Recognition Based on Word Fusion of Graph Attention Network [PDF]
Jisuanji gongcheng, 2022 Named entity recognition refers to the recognition of entities with specific meanings in texts.It is an important cornerstone of many downstream tasks in natural language processing.In the task of named entity recognition, the Collaborative Graph Network
SONG Xuhui, YU Hongtao, LI Shaomei
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Constructing marine expert management knowledge graph based on Trellisnet-CRF [PDF]
PeerJ Computer Science, 2022 Creating and maintaining a domain-specific database of research institutions, academic experts and scholarly literature is essential to expanding national marine science and technology.
Jiajing Wu +5 more
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Dictionary-based matching graph network for biomedical named entity recognition
Scientific Reports, 2023 Biomedical named entity recognition (BioNER) is an essential task in biomedical information analysis. Recently, deep neural approaches have become widely utilized for BioNER.
Yinxia Lou, Xun Zhu, Kai Tan
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Vulnerability Evaluation Algorithm Based on BNAG Model [PDF]
Jisuanji gongcheng, 2019 In order to accurately evaluate the vulnerability of computer network,a new evaluation algorithm is proposed by combining Bayesian network with attack graph.An attack graph model is constructed,which is named RSAG.On the basis of eliminating the loop in ...
WANG Hui, LOU Yalong, DAI Tianwang, RU Xinxin, LIU Kun
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Graph Ranking for Collective Named Entity Disambiguation [PDF]
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2014 Named Entity Disambiguation (NED) refers to the task of mapping different named entity mentions in running text to their correct interpretations in a specific knowledge base (KB). This paper presents a collective disambiguation approach using a graph model.
Ayman Alhelbawy, Robert Gaizauskas
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A Multi-Granular Aggregation-Enhanced Knowledge Graph Representation for Recommendation
Information, 2022 Knowledge graph (KG) helps to improve the accuracy, diversity, and interpretability of a recommender systems. KG has been applied in recommendation systems, exploiting graph neural networks (GNNs), but most existing recommendation models based on GNNs ...
Xi Liu, Rui Song, Yuhang Wang, Hao Xu
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