Results 241 to 250 of about 316,892 (282)

Generative named entity recognition framework for Chinese legal domain. [PDF]

PeerJ Comput Sci
Mao X, Jiang J, Zeng Y, Peng Y, Zhang S, Li F.   +5 more
europepmc   +1 more source

Named entity recognition of pharmacokinetic parameters in the scientific literature. [PDF]

Sci Rep
Gonzalez Hernandez F, Nguyen Q, Smith VC, Cordero JA, Ballester MR, Duran M, Solé A, Chotsiri P, Wattanakul T, Mundin G, Lilaonitkul W, Standing JF, Kloprogge F.   +12 more
europepmc   +1 more source

A text-speech multimodal Chinese named entity recognition model for crop diseases and pests. [PDF]

Sci Rep
Liu R, Guo X, Zhu H, Wang L.
europepmc   +1 more source

A Position- and Similarity-Aware Named Entity Recognition Model for Power Equipment Maintenance Work Orders. [PDF]

Sensors (Basel)
Wei Z, Qu S, Zhao L, Shi Q, Zhang C.
europepmc   +1 more source

MAHE: a multiscale and hybrid expert-based model for image-text enhanced named entity recognition on social media. [PDF]

Sci Rep
Yang S, Mo B, Liu D, Zhu L.
europepmc   +1 more source

Attention-based interactive multi-level feature fusion for named entity recognition. [PDF]

Sci Rep
Xu Y, Chen Y.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Named entity recognition for tweets

ACM Transactions on Intelligent Systems and Technology, 2013
Two main challenges of Named Entity Recognition (NER) for tweets are the insufficient information in a tweet and the lack of training data. We propose a novel method consisting of three core elements: (1) normalization of tweets; (2) combination of a K-Nearest Neighbors (KNN) classifier with a linear Conditional Random Fields (CRF) model; and (3 ...
Xiaohua Liu, Furu Wei, Shaodian Zhang, Ming Zhou 0001   +3 more
openaire   +1 more source

Named-Entity Recognition in Bengali

Post-Proceedings of the 4th and 5th Workshops of the Forum for Information Retrieval Evaluation, 2013
This paper describes two systems for Named Entity Recognition (NER) and performance of two systems has been compared. The first system is a rule-based one whereas the second one is statistical (based on CRF) in nature. The systems vary in some other aspects too, for example, the first system works on untagged data (not even POS tag is done) to identify
Apurbalal Senapati, Arjun Das, Utpal Garain   +2 more
openaire   +1 more source

A Survey on Named Entity Recognition

2020
Natural language processing is an important research direction and research hotspot in the field of artificial intelligence. Named entity recognition is one of the key tasks, which is to identify entities with specific meanings in the text, such as names of people, places, institutions, proper nouns, etc.
Yan Wen 0002, Cong Fan, Geng Chen 0002, Xin Chen 0079, Ming Chen 0001   +4 more
openaire   +1 more source