Results 221 to 230 of about 19,275 (267)

Elaborating the Motivations and Attitudes Driving Interest in Voluntary Biodiversity Credits

Business Strategy and the Environment, EarlyView.
ABSTRACT Global biodiversity loss has prompted the search for new sources of conservation finance, such as voluntary biodiversity credits (VBCs). However, despite optimistic market projections, current uptake of VBCs is limited. Adopting an interpretive approach, we analyse 21 semistructured interviews with early market actors (buyers, sellers ...
Gamze Yakar‐Pritchard, Andrew Greenman, Stacia Stetkiewicz, Bouwe Dijkstra, Frances Bowen, Richard Field   +5 more
wiley   +1 more source

Enhancing and Not Replacing Clinical Expertise: Improving Named-Entity Recognition in Colonoscopy Reports Through Mixed Real-Synthetic Training Sources. [PDF]

J Pers Med
Ioanovici AC, Feier AM, Mărușteri MȘ, Trâmbițaș-Miron AD, Dobru DE.   +4 more
europepmc   +1 more source

Enhancing biomedical named entity recognition with parallel boundary detection and category classification. [PDF]

BMC Bioinformatics
Wang Y, Tong H, Zhu Z, Hou F, Li Y.
europepmc   +1 more source

Chinese medical named entity recognition utilizing entity association and gate context awareness. [PDF]

PLoS One
Yan Y, Kang Y, Huang W, Cai X.
europepmc   +1 more source

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

GRU-SCANET: unleashing the power of GRU-based sinusoidal capture network for precision-driven named entity recognition. [PDF]

Bioinform Adv
Happi Happi BG, Pelap GF, Symeonidou D, Larmande P.   +3 more
europepmc   +1 more source

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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

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