Results 61 to 70 of about 177,864 (288)

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Named Entity Recognition Based on Multi-scale Attention [PDF]

Jisuanji kexue yu tansuo
The accuracy of named entity recognition (NER) task will promote the research of multiple downstream tasks in natural language field. Due to a large number of nested semantics in text, named entities are recognized difficultly.
TANG Ruixue, QIN Yongbin, CHEN Yanping
doaj   +1 more source

A Survey of Location Prediction on Twitter

, 2018
Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for decades.
Han, Jialong, Sun, Aixin, Zheng, Xin
core   +1 more source

Named Entity Recognition Datasets: A Classification Framework

International Journal of Computational Intelligence Systems
Named entity recognition as a fundamental task plays a crucial role in accomplishing some of the tasks and applications in natural language processing. In the age of Internet information, as far as computer applications are concerned, a huge proportion ...
Ying Zhang, Gang Xiao
semanticscholar   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Entity Span Suffix Classification for Nested Chinese Named Entity Recognition

Information
Named entity recognition (NER) is one of the fundamental tasks in building knowledge graphs. For some domain-specific corpora, the text descriptions exhibit limited standardization, and some entity structures have entity nesting.
Jianfeng Deng, Ruitong Zhao, Wei Ye, Suhong Zheng   +3 more
doaj   +1 more source

Named entity tagging a very large unbalanced corpus: training and evaluating NE classifiers [PDF]

, 2014
We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging
Bingel, Joachim, Haider, Thomas
core  

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Research on Named Entity Recognition Technology in Military Software Testing

Jisuanji kexue yu tansuo, 2020
Named entity recognition is an important stage in the construction of knowledge graph. Based on the national military standard and software testing documents, the entity type classification and the data set construction and labeling are completed. In the
HAN Xinxin, BEN Kerong, ZHANG Xian
doaj   +1 more source

Decomposed Two-Stage Prompt Learning for Few-Shot Named Entity Recognition

Information, 2023
Named entity recognition (NER) in a few-shot setting is an extremely challenging task, and most existing methods fail to account for the gap between NER tasks and pre-trained language models.
Feiyang Ye, Liang Huang, Senjie Liang, KaiKai Chi   +3 more
doaj   +1 more source