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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...
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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...
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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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Dominik Warch, Patrick Stellbauer and Pascal Neis
In the digital transformation era, video media libraries? untapped potential is immense, restricted primarily by their non-machine-readable nature and basic search functionalities limited to standard metadata. This study presents a novel multimodal metho...
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Tahir Mehmood, Ivan Serina, Alberto Lavelli, Luca Putelli and Alfonso Gerevini
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online data is...
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Xiaolong Li, Wu Zhang, Yanjie Wang, Yongbin Tan and Jing Xia
As an important carrier of individual information, the resume is an important data source for studying the spatio-temporal evolutionary characteristics of individual and group behaviors. This study focuses on spatio-temporal information extraction and ge...
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Wei Zhang, Jingtao Meng, Jianhua Wan, Chengkun Zhang, Jiajun Zhang, Yuanyuan Wang, Liuchang Xu and Fei Li
Social media is widely used to share real-time information and report accidents during natural disasters. Named entity recognition (NER) is a fundamental task of geospatial information applications that aims to extract location names from natural languag...
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Demeng Zhang, Guang Zheng, Hebing Liu, Xinming Ma and Lei Xi
Chinese named entity recognition of wheat diseases and pests is an initial and key step in constructing knowledge graphs. In the field of wheat diseases and pests, there are problems, such as lack of training data, nested entities, fuzzy entity boundarie...
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Weiwei Sun, Shengquan Liu, Yan Liu, Lingqi Kong and Zhaorui Jian
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Qiang He, Guowei Chen, Wenchao Song and Pengzhou Zhang
Named entity recognition (NER) is a subfield of natural language processing (NLP) that identifies and classifies entities from plain text, such as people, organizations, locations, and other types. NER is a fundamental task in information extraction, inf...
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