110   Artículos

 
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

 
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
Boris Stanoev, Goran Mitrov, Andrea Kulakov, Georgina Mirceva, Petre Lameski and Eftim Zdravevski    
With the exponential growth of data, extracting actionable insights becomes resource-intensive. In many organizations, normalized relational databases store a significant portion of this data, where tables are interconnected through some relations. This ... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Malgorzata Olszowy-Tomczyk and Dorota Wianowska    
Concern for the future of the next generation leads to the search for alternative solutions for the proper management of materials considered as useless waste. This study fits into this research trend. Its aim is to demonstrate the potential of walnut hu... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li    
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Qiuyue Li, Hao Sheng, Mingxue Sheng and Honglin Wan    
Efficient document recognition and sharing remain challenges in the healthcare, insurance, and finance sectors. One solution to this problem has been the use of deep learning techniques to automatically extract structured information from paper documents... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Ning Yu, Jianyi Liu and Yu Shi    
With the development of information extraction technology, a variety of entity-relation extraction paradigms have been formed. However, approaches guided by these existing paradigms suffer from insufficient information fusion and too coarse extraction gr... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Mihael Arcan, Sampritha Manjunath, Cécile Robin, Ghanshyam Verma, Devishree Pillai, Simon Sarkar, Sourav Dutta, Haytham Assem, John P. McCrae and Paul Buitelaar    
Intent classification is an essential task for goal-oriented dialogue systems for automatically identifying customers? goals. Although intent classification performs well in general settings, domain-specific user goals can still present a challenge for t... ver más
Revista: Information    Formato: Electrónico

 
en línea
Ayiguli Halike, Aishan Wumaier and Tuergen Yibulayin    
Although low-resource relation extraction is vital in knowledge construction and characterization, more research is needed on the generalization of unknown relation types. To fill the gap in the study of low-resource (Uyghur) relation extraction methods,... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yuhe Sun, Zuohua Ding, Hongyun Huang, Senhao Zou and Mingyue Jiang    
Relation extraction (RE) is a fundamental NLP task that aims to identify relations between some entities regarding a given text. RE forms the basis for many advanced NLP tasks, such as question answering and text summarization, and thus its quality is cr... ver más
Revista: Algorithms    Formato: Electrónico

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