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Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu...
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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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Elie Azeraf, Emmanuel Monfrini and Wojciech Pieczynski
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propose tw...
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Lin He, Shengnan Wang and Xinran Cao
Shipping Enterprise Credit Named Entity Recognition (NER) aims to recognize shipping enterprise credit entities from unstructured shipping enterprise credit texts. Aiming at the problem of low entity recognition rate caused by complex and diverse entitie...
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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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Petros Vahamidis, Angeliki Stefopoulou and Vassilis Kotoulas
Nitrogen (N) fertilisers used in barley production serve as the primary contributors to total greenhouse gas (GHG) emissions. Consequently, to lower the carbon footprint (CF) and GHG emissions, it is imperative to either reduce N fertiliser rates or enha...
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Xiaohui Cui, Yu Yang, Dongmei Li, Xiaolong Qu, Lei Yao, Sisi Luo and Chao Song
Recently, researchers have extensively explored various methods for electronic medical record named entity recognition, including character-based, word-based, and hybrid methods. Nonetheless, these methods frequently disregard the semantic context of ent...
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Sardar Parhat, Mutallip Sattar, Askar Hamdulla and Abdurahman Kadir
In this study, based on a morpheme segmentation framework, we researched a text keyword extraction method for Uyghur, Kazakh and Kirghiz languages, which have similar grammatical and lexical structures. In these languages, affixes and a stem are joined t...
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Tahir Mehmood, Alfonso E. Gerevini, Alberto Lavelli, Matteo Olivato and Ivan Serina
Single-task models (STMs) struggle to learn sophisticated representations from a finite set of annotated data. Multitask learning approaches overcome these constraints by simultaneously training various associated tasks, thereby learning generic represen...
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Chengkun Zhang, Yiran Zhang, Jiajun Zhang, Junwei Yao, Hongjiu Liu, Tao He, Xinyu Zheng, Xingyu Xue, Liang Xu, Jing Yang, Yuanyuan Wang and Liuchang Xu
In recent years, the Chinese tourism industry has developed rapidly, leading to significant changes in the relationship between people and space patterns in scenic regions. To attract more tourists, the surrounding environment of a scenic region is usual...
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