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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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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...
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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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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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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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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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Kokoy Siti Komariah, Ariana Tulus Purnomo, Ardianto Satriawan, Muhammad Ogin Hasanuddin, Casi Setianingsih and Bong-Kee Sin
To pursue a healthy lifestyle, people are increasingly concerned about their food ingredients. Recently, it has become a common practice to use an online recipe to select the ingredients that match an individual?s meal plan and healthy diet preference. T...
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Yeon-Ji Park, Min-a Lee, Geun-Je Yang, Soo Jun Park and Chae-Bong Sohn
The BioBERT Named Entity Recognition (NER) model is a high-performance model designed to identify both known and unknown entities. It surpasses previous NER models utilized by text-mining tools, such as tmTool and ezTag, in effectively discovering novel ...
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