A survey of CRF algorithm based knowledge extraction of elementary mathematics in Chinese
S Liu, T He, J Dai - Mobile Networks and Applications, 2021 - Springer
Chinese word segmentation is an important research direction in related research on
elementary mathematics knowledge extraction. The speed of segmentation directly affects …
elementary mathematics knowledge extraction. The speed of segmentation directly affects …
Deep learning-based extraction of construction procedural constraints from construction regulations
Construction procedural constraints are critical in facilitating effective construction procedure
checking in practice and for various inspection systems. Nowadays, the manual extraction of …
checking in practice and for various inspection systems. Nowadays, the manual extraction of …
[PDF][PDF] A fake news detection system based on combination of word embedded techniques and hybrid deep learning model
At present, most people prefer using different online sources for reading news. These
sources can easily spread fake news for several malicious reasons. Detecting this unreliable …
sources can easily spread fake news for several malicious reasons. Detecting this unreliable …
Deep learning algorithms to identify documentation of serious illness conversations during intensive care unit admissions
Background: Timely documentation of care preferences is an endorsed quality indicator for
seriously ill patients admitted to intensive care units. Clinicians document their …
seriously ill patients admitted to intensive care units. Clinicians document their …
Bidirectional recurrent neural network approach for Arabic named entity recognition
Recurrent neural network (RNN) has achieved remarkable success in sequence labeling
tasks with memory requirement. RNN can remember previous information of a sequence …
tasks with memory requirement. RNN can remember previous information of a sequence …
Bilstm-crf manipuri ner with character-level word representation
L Jimmy, K Nongmeikappam, SK Naskar - Arabian Journal for Science and …, 2023 - Springer
Abstract Named Entity Recognition and Classification (NER) serves as a foundation for
many natural language processing tasks such as question answering, text summarization …
many natural language processing tasks such as question answering, text summarization …
Unsupervised dialogue intent detection via hierarchical topic model
A Popov, V Bulatov, D Polyudova… - Proceedings of the …, 2019 - aclanthology.org
One of the challenges during a task-oriented chatbot development is the scarce availability
of the labeled training data. The best way of getting one is to ask the assessors to tag each …
of the labeled training data. The best way of getting one is to ask the assessors to tag each …
Multilingual named entity recognition based on the BiGRU-CNN-CRF hybrid model
M Ayifu, S Wushouer, M Palidan - International Journal of …, 2019 - inderscienceonline.com
Uyghur, Kazak, and Kyrgyz (UKK languages) are agglutinative and low-resource languages
with rich morphological features. Determining how to obtain a better general entity …
with rich morphological features. Determining how to obtain a better general entity …
Robust to noise models in natural language processing tasks
V Malykh - Proceedings of the 57th Annual Meeting of the …, 2019 - aclanthology.org
There are a lot of noise texts surrounding a person in modern life. The traditional approach
is to use spelling correction, yet the existing solutions are far from perfect. We propose …
is to use spelling correction, yet the existing solutions are far from perfect. We propose …
Named entity recognition in noisy domains
Named Entity Recognition (NER) task is an important part for conversational AI. A typical
user of a conversation system has no time to check the spelling or grammar in his or her …
user of a conversation system has no time to check the spelling or grammar in his or her …