A review of Chinese named entity recognition.
Abstract Named Entity Recognition (NER) is used to identify entity nouns in the corpus such
as Location, Person and Organization, etc. NER is also an important basic of research in …
as Location, Person and Organization, etc. NER is also an important basic of research in …
An end-to-end progressive multi-task learning framework for medical named entity recognition and normalization
Medical named entity recognition (NER) and normalization (NEN) are fundamental for
constructing knowledge graphs and building QA systems. Existing implementations for …
constructing knowledge graphs and building QA systems. Existing implementations for …
[HTML][HTML] FindVehicle and VehicleFinder: a NER dataset for natural language-based vehicle retrieval and a keyword-based cross-modal vehicle retrieval system
Natural language (NL) based vehicle retrieval is a task aiming to retrieve a vehicle that is
most consistent with a given NL query from among all candidate vehicles. Because NL …
most consistent with a given NL query from among all candidate vehicles. Because NL …
Named entity recognition using word embedding as a feature
This study applied word embedding to feature for named entity recognition (NER) training,
and used CRF as a learning algorithm. Named entities are phrases that contain the names …
and used CRF as a learning algorithm. Named entities are phrases that contain the names …
[HTML][HTML] On the use of parsing for named entity recognition
Parsing is a core natural language processing technique that can be used to obtain the
structure underlying sentences in human languages. Named entity recognition (NER) is the …
structure underlying sentences in human languages. Named entity recognition (NER) is the …
MTAAL: multi-task adversarial active learning for medical named entity recognition and normalization
Automated medical named entity recognition and normalization are fundamental for
constructing knowledge graphs and building QA systems. When it comes to medical text, the …
constructing knowledge graphs and building QA systems. When it comes to medical text, the …
Investigating annotation noise for named entity recognition
Recent studies revealed that even the most widely used benchmark dataset still contains
more than 5% sample-level annotation noise in Named Entity Recognition (NER). Hence …
more than 5% sample-level annotation noise in Named Entity Recognition (NER). Hence …
Chinese named entity recognition with conditional random fields in the light of chinese characteristics
This paper introduces the research works of Chinese named entity recognition (CNER)
including person name, organization name and location name. To differ from the …
including person name, organization name and location name. To differ from the …
BiLSTM-based with word-weight attention for Chinese named entity recognition
Z Chen, R Qi, S Li - 2022 IEEE 13th International Conference …, 2022 - ieeexplore.ieee.org
Natural language processing is a hot research area in recent years. Named entity
recognition is a fundamental task in natural language processing. However, Chinese named …
recognition is a fundamental task in natural language processing. However, Chinese named …
[PDF][PDF] Comparison of NER performance using word embeddings
MR Seok, HJ Song, CY Park, JD Kim… - The 4th international …, 2015 - researchgate.net
Recent studies in NER use the supervised machine learning. This study used CRF as a
learning algorithm, and applied word embedding to feature for NER training. Word …
learning algorithm, and applied word embedding to feature for NER training. Word …