255   Artículos

 
en línea
Qishun Mei and Xuhui Li    
To address the limitations of existing methods of short-text entity disambiguation, specifically in terms of their insufficient feature extraction and reliance on massive training samples, we propose an entity disambiguation model called COLBERT, which f... ver más
Revista: Information    Formato: Electrónico

 
en línea
Weijun Li, Jintong Liu, Yuxiao Gao, Xinyong Zhang and Jianlai Gu    
The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is ca... ver más
Revista: Applied System Innovation    Formato: Electrónico

 
en línea
Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan    
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Marie-Therese Charlotte Evans, Majid Latifi, Mominul Ahsan and Julfikar Haider    
Keyword extraction from Knowledge Bases underpins the definition of relevancy in Digital Library search systems. However, it is the pertinent task of Joint Relation Extraction, which populates the Knowledge Bases from which results are retrieved. Recent ... ver más
Revista: Information    Formato: Electrónico

 
en línea
Adedamola Adesokan, Rowan Kinney and Eirini Eleni Tsiropoulou    
This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH ... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Mikael Sabuhi, Petr Musilek and Cor-Paul Bezemer    
As the number of machine learning applications increases, growing concerns about data privacy expose the limitations of traditional cloud-based machine learning methods that rely on centralized data collection and processing. Federated learning emerges a... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Lianlian He, Hao Li and Rui Zhang    
Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeferen... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Shilei Cao, Man Yang and Jian Liu    
Due to its advantages of easy deployment and high stiffness-to-mass ratio, the utilization of truss structures for constructing large satellites presents an appealing solution for modern space missions, including Earth observation and astronomy. However,... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Yue Zha, Yuanzhi Ke, Xiao Hu and Caiquan Xiong    
Named entity recognition (NER) is particularly challenging for medical texts due to the high domain specificity, abundance of technical terms, and sparsity of data in this field. In this work, we propose a novel attention layer, called the ?ontology atte... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Lingqi Kong and Shengquau Liu    
With the development of the Internet, vast amounts of text information are being generated constantly. Methods for extracting the valuable parts from this information have become an important research field. Relation extraction aims to identify entities ... ver más
Revista: Applied Sciences    Formato: Electrónico

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