Results 21 to 30 of about 25,867,085 (318)
ORCID-linked labeled data for evaluating author name disambiguation at scale [PDF]
Scientometrics, 2021 How can we evaluate the performance of a disambiguation method implemented on big bibliographic data? This study suggests that the open researcher profile system, ORCID, can be used as an authority source to label name instances at scale.
Jinseok Kim, Jason Owen-Smith
semanticscholar +1 more source
Quality Estimation without Human-labeled Data [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Quality estimation aims to measure the quality of translated content without access to a reference translation. This is crucial for machine translation systems in real-world scenarios where high-quality translation is needed.
Yi-Lin Tuan +5 more
semanticscholar +1 more source
Seismic labeled data expansion using variational autoencoders
Artificial Intelligence in Geosciences, 2020 Supervised machine learning algorithms have been widely used in seismic exploration processing, but the lack of labeled examples complicates its application.
Kunhong Li, Song Chen, Guangmin Hu, Ph.D
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You Don’t Need Labeled Data for Open-Book Question Answering
Applied Sciences, 2021 Open-book question answering is a subset of question answering (QA) tasks where the system aims to find answers in a given set of documents (open-book) and common knowledge about a topic.
Sia Gholami, Mehdi Noori
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Weighted Pseudo Labeled Data and Mutual Learning for Semi-Supervised Classification
IEEE Access, 2021 In this article, a semi-supervised classification algorithm that is based on weighted pseudo labeled data and mutual learning is proposed. The purpose of our method is to improve the classification performance of semi-supervised learning models and ...
Jianwen Mo, Yuwan Gan, Hua Yuan
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A residential labeled dataset for smart meter data analytics
Scientific Data, 2022 Measurement(s) Electricity Consumption Technology Type(s) Transformer Device Sample Characteristic - Location ...
Lucas Pereira +2 more
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Improved Machine Reading Comprehension Using Data Validation for Weakly Labeled Data
IEEE Access, 2020 Machine reading comprehension (MRC) is a natural language processing task wherein a given question is answered according to a holistic understanding of a given context.
Yunyeong Yang, Sangwoo Kang, Jungyun Seo
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Distant supervision for relation extraction without labeled data
Annual Meeting of the Association for Computational Linguistics, 2009 Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that does not require labeled corpora, avoiding the domain dependence of ACE ...
Mike D. Mintz +3 more
semanticscholar +1 more source
GAN-BElectra: Enhanced Multi-class Sentiment Analysis with Limited Labeled Data
Applied Artificial Intelligence, 2022 Performing sentiment analysis with high accuracy using machine-learning techniques requires a large quantity of training data. However, getting access to such a large quantity of labeled data for specific domains can be expensive and time-consuming ...
Md. Riyadh, M. Omair Shafiq
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Application of biclustering algorithm to extract rules from labeled data [PDF]
International Journal of Crowd Science, 2018 Purpose - For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure.
Zhang Yanjie, Sun Hongbo
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