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Academic Articles & Research Papers
Showing 18 of 18 academic articles
Yijun Xiao, William Yang Wang • Proceedings of the AAAI Conference on Artificial Intelligence
(2019)
Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable. In this paper,...
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Open Access
DOI: https://doi.org/10.1609/aaai.v33i01.33017322
Aleš Horák, Adam Rambousek • Routledge eBooks
(2017)
The chapter introduces links between lexicography and natural language processing in both directions. First, how the lexicographic work benefits from techniques of natural language processing such as word sense disambiguation, semantic simi...
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DOI: https://doi.org/10.4324/9781315104942-13
Yang Liu, Meng Zhang • Computational Linguistics
(2017)
Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...
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cc-by-nc-nd
DOI: https://doi.org/10.1162/coli_r_00312
Fredrik Olsson • KTH Publication Database DiVA (KTH Royal Institute of Technology)
(2009)
Active learning is a supervised machine learning technique in which the learner is in control of the data used for learning. That control is utilized by the learner to ask an oracle, typically a human with extensive knowledge of the domain ...
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Sonit Singh • arXiv (Cornell University)
(2018)
With rise of digital age, there is an explosion of information in the form of news, articles, social media, and so on. Much of this data lies in unstructured form and manually managing and effectively making use of it is tedious, boring and...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1807.02383
Gonçalo Carnaz, Vitor Beires Nogueira, Mário Antunes • Informatics
(2021)
Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to man...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/informatics8020037
Jantima Polpinij, Manasawee Kaenampornpan, Christopher S. G. Khoo, Wei-Ning Cheng et al. • Mathematics
(2026)
Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math14020299
Hind Alamro, Takashi Gojobori, Magbubah Essack, Xin Gao • Scientific Reports
(2024)
Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-58334-x
Nadia Mushtaq Gardazi, Ali Yusny Daud, Muhammad Kamran Malik, Amal Abdullah Bukhari et al. • Artificial Intelligence Review
(2025)
BERT (Bidirectional Encoder Representations from Transformers) has revolutionized Natural Language Processing (NLP) by significantly enhancing the capabilities of language models. This review study examines the complex nature of BERT, inclu...
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cc-by-nc-nd
DOI: https://doi.org/10.1007/s10462-025-11162-5
Miao Jiang, Honghui Chen • Applied Sciences
(2025)
Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15052521
裕二 池谷, Robert Tinn, Hao Cheng, MICHAEL A. LUCAS et al. • ACM Transactions on Computing for Healthcare
(2021)
Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...
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Open Access
DOI: https://doi.org/10.1145/3458754
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton et al. • Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo)
(2020)
We introduce Sta n z a , an open-source Python natural language processing toolkit supporting 66 human languages.Compared to existing widely used toolkits, Sta n z a features a language-agnostic fully neural pipeline for text analysis, incl...
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cc-by
DOI: https://doi.org/10.18653/v1/2020.acl-demos.14
Zabir Al Nazi, Wei Peng • Informatics
(2024)
The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable ability to provide proficient responses to free-text queries, demonstrating a nuan...
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Open Access (DOAJ)
DOI: 10.3390/informatics11030057
Tianxiang Sun, Xiang-Yang Liu, Xipeng Qiu, Xuanjing Huang • Machine Intelligence Research
(2022)
Abstract In the era of deep learning, modeling for most natural language processing (NLP) tasks has converged into several mainstream paradigms. For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as...
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cc-by
DOI: https://doi.org/10.1007/s11633-022-1331-6
Wazir Ali, Jay Kumar, Zenglin Xu, Rajesh Kumar et al. • Applied Sciences
(2021)
Named entity recognition (NER) is a fundamental task in many natural language processing (NLP) applications, such as text summarization and semantic information retrieval. Recently, deep neural networks (NNs) with the attention mechanism yi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app11199038
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen et al. • arXiv (Cornell University)
(2011)
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1103.0398
Kai Wang, Kunjian Wen, Yanping Chen, Yongbin Qin • Scientific Reports
(2025)
Abstract Mapping a sentence into a two-dimensional (2D) representation can flatten nested semantic structures and build multi-granular span dependencies in named entity recognition. Existing approaches to recognizing named entities often cl...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-87722-0
Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering
(2020)
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981314