Results 1 to 10 of about 177,864 (288)
A Survey of Arabic Named Entity Recognition and Classification [PDF]
Computational Linguistics, 2021 As more and more Arabic textual information becomes available through the Web in homes and businesses, via Internet and Intranet services, there is an urgent need for technologies and tools to process the relevant information. Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural ...
Khaled Shaalan
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Information, 2022 Intent classification and named entity recognition of medical questions are two key subtasks of the natural language understanding module in the question answering system.
Turdi Tohti +2 more
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Kannada Named Entity Recognition and Classification (NERC) Based on Multinomial Naïve Bayes (MNB) Classifier [PDF]
International Journal on Natural Language Computing, 2015 14 pages, 3 figures, International Journal on Natural Language Computing (IJNLC) Vol.
Amarappa, S., Sathyanarayana, S. V.
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BMC BioinformaticsBackground Named entity recognition is a fundamental task in natural language processing. Recognizing entities in biomedical text, known as the BioNER, is particularly crucial for cutting-edge applications.
Yu Wang +4 more
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Does semantics aid syntax? An empirical study on named entity recognition and classification
Neural Computing and Applications, 2021 Many researchers jointly model multiple linguistic tasks (e.g., joint modeling of named entity recognition and named entity classification and joint modeling of syntactic parsing and semantic parsing) with an implicit assumption that these individual tasks can enhance each other via the joint modeling.
Xiaoshi Zhong +2 more
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Named Entity Recognition and Classification in Historical Documents: A Survey [PDF]
ACM Computing Surveys, 2023 After decades of massive digitisation, an unprecedented number of historical documents are available in digital format, along with their machine-readable texts. While this represents a major step forward with respect to preservation and accessibility, it also opens up new opportunities in terms of content mining and the next fundamental challenge is to
Maud Ehrmann +4 more
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Leveraging Type Descriptions for Zero-shot Named Entity Recognition and Classification [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 A common issue in real-world applications of named entity recognition and classification (NERC) is the absence of annotated data for target entity classes during training. Zeroshot learning approaches address this issue by learning models that can transfer information from observed classes in the training data to unseen classes. This paper presents the
Aly, Rami +2 more
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Incorporating rich background knowledge for gene named entity classification and recognition [PDF]
BMC Bioinformatics, 2009 Background Gene named entity classification and recognition are crucial preliminary steps of text mining in biomedical literature. Machine learning based methods have been used in this area with great success.
Yang Zhihao, Lin Hongfei, Li Yanpeng
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Journal of Information Systems Engineering and Business IntelligenceBackground: Understanding human language is a part of the research in Natural Language Processing (NLP) known as Natural Language Understanding (NLU). It becomes a crucial part of some NLP applications such as chatbots, that interpret the user intent and
Rizal Setya Perdana, Putra Pandu Adikara
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Few-shot classification in Named Entity Recognition Task [PDF]
ACM Symposium on Applied Computing, 2018 For many natural language processing (NLP) tasks the amount of annotated data is limited. This urges a need to apply semi-supervised learning techniques, such as transfer learning or meta-learning.
Akhundov Adnan +5 more
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