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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 ...
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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 ...
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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 ...
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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...
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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...
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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...
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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...
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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...
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Jaskaran Gill, Madhu Chetty, Suryani Lim and Jennifer Hallinan
Relation extraction from biological publications plays a pivotal role in accelerating scientific discovery and advancing medical research. While vast amounts of this knowledge is stored within the published literature, extracting it manually from this co...
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Yaqin Zhu, Xuhang Li, Zijian Wang, Jiayong Li, Cairong Yan and Yanting Zhang
In recent years, joint entity?relation extraction (ERE) models have become a hot research topic in natural language processing (NLP). Several studies have proposed a span-based ERE framework, which utilizes simple span embeddings for entity and relation ...
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