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Jonghyeon Yang, Hanme Jang and Kiyun Yu
In recent years, question answering on knowledge bases (KBQA) has emerged as a promising approach for providing unified, user-friendly access to knowledge bases. Nevertheless, existing KBQA systems struggle to answer spatial-related questions, prompting ...
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Botao Zhang, Yong Feng, Lin Fu, Jinguang Gu and Fangfang Xu
Entity and relation linking are the core tasks in knowledge base question answering (KBQA). They connect natural language questions with triples in the knowledge base. In most studies, researchers perform these two tasks independently, which ignores the ...
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Noura Maghawry, Samy Ghoniemy, Eman Shaaban and Karim Emara
Semantic data integration provides the ability to interrelate and analyze information from multiple heterogeneous resources. With the growing complexity of medical ontologies and the big data generated from different resources, there is a need for integr...
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Mamatjan Abdurxit, Turdi Tohti and Askar Hamdulla
Biomedical entity linking is an important research problem for many downstream tasks, such as biomedical intelligent question answering, information retrieval, and information extraction. Biomedical entity linking is the task of mapping mentions in medic...
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Qijia Li, Feng Li, Shuchao Li, Xiaoyu Li, Kang Liu, Qing Liu and Pengcheng Dong
Entity linking involves mapping ambiguous mentions in documents to the correct entities in a given knowledge base. Most of the current methods are a combination of local and global models. The local model uses the local context information around the ent...
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Lei Gao, Lijuan Zhang, Lei Zhang and Jie Huang
With the explosive growth in short texts on the Web and an increasing number of Web corpora consisting of short texts, short texts are playing an important role in various Web applications. Entity linking is a crucial task in knowledge graphs and a key t...
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Yang Zhang, Jin Liu, Bo Huang and Bei Chen
Entity linking plays a fundamental role in knowledge engineering and data mining and is the basis of various downstream applications such as content analysis, relationship extraction, question and answer. Most existing entity linking models rely on suffi...
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Alexander Sboev, Roman Rybka, Artem Gryaznov, Ivan Moloshnikov, Sanna Sboeva, Gleb Rylkov and Anton Selivanov
Mapping the pharmaceutically significant entities on natural language to standardized terms/concepts is a key task in the development of the systems for pharmacovigilance, marketing, and using drugs out of the application scope. This work estimates the a...
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Michael Angelos Simos and Christos Makris
The induction of the semantics of unstructured text corpora is a crucial task for modern natural language processing and artificial intelligence applications. The Named Entity Disambiguation task comprises the extraction of Named Entities and their linki...
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Mayank Kejriwal
Entity Resolution (ER) is the problem of identifying co-referent entity pairs across datasets, including knowledge graphs (KGs). ER is an important prerequisite in many applied KG search and analytics pipelines, with a typical workflow comprising two ste...
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