On the public citation graph

An Arabic Dataset for Disease Named Entity Recognition with Multi-Annotation Schemes

https://doi.org/10.3390/data5030060
0 signed · 22 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-24033-6_7openalex-snapshot
Segment Representations in Named Entity Recognition
inferredcites →https://doi.org/10.1007/978-3-319-52920-2_18openalex-snapshot
Combining Knowledge and CRF-Based Approach to Named Entity Recognition in Russian
inferredcites →https://doi.org/10.1007/978-3-540-85287-2_42openalex-snapshot
Arabic Named Entity Recognition from Diverse Text Types
inferredcites →https://doi.org/10.1145/3383306openalex-snapshot
Named Entity Recognition and Classification for Punjabi Shahmukhi
inferredcites →https://doi.org/10.11613/bm.2012.031openalex-snapshot
Interrater reliability: the kappa statistic
inferredcites →https://doi.org/10.1162/coli_a_00178openalex-snapshot
A Survey of Arabic Named Entity Recognition and Classification
inferredcites →https://doi.org/10.1177/001316446002000104openalex-snapshot
A Coefficient of Agreement for Nominal Scales
inferredcites →https://doi.org/10.4324/9780203880746openalex-snapshot
Colloquial Arabic (Levantine)
inferredcites →https://doi.org/10.63317/2zrdshx39mu4openalex-snapshot
Named Entity Recognition in Greek Texts
inferredcites →https://doi.org/10.63317/3piegahzyagxopenalex-snapshot
MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s13278-024-01294-xopenalex-snapshot
Hybrid annotation and classification for predicting attitudes towards COVID-19 vaccines for Arabic tweets
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.120489openalex-snapshot
Shahmukhi named entity recognition by using contextualized word embeddings
inferred← citeshttps://doi.org/10.1016/j.procs.2022.07.109openalex-snapshot
Arabic Named Entity Recognition in Arabic Tweets Using BERT-based Models
inferred← citeshttps://doi.org/10.1016/j.procs.2026.01.072openalex-snapshot
A rule-based model with Fuzzy matching for disease named entity recognition in Arabic biomedical texts
inferred← citeshttps://doi.org/10.1088/1757-899x/1003/1/012156openalex-snapshot
A method for constructing a dataset to reveal the industrial behaviour of big data
inferred← citeshttps://doi.org/10.1109/i-smac58438.2023.10290283openalex-snapshot
An Efficient Approach of NER in Social Media using BiLSTM-CRF Model
inferred← citeshttps://doi.org/10.1109/imsa58542.2023.10217658openalex-snapshot
Named Entity Recognition for Arabic Medical Texts Using Deep Learning Models
inferred← citeshttps://doi.org/10.11591/ijeecs.v27.i3.pp1589-1600openalex-snapshot
Towards an approach based on particle swarm optimization for Arabic named entity recognition on social media
inferred← citeshttps://doi.org/10.1177/2167647x251409135openalex-snapshot
Real-Time Named Entity Recognition from Textual Electronic Clinical Records in Cancer Therapy Using Low-Latency Neural Networks
inferred← citeshttps://doi.org/10.21608/bjas.2024.279914.1377openalex-snapshot
Advancing Arabic Scientific Text Analysis: Evaluating Machine Learning Models for Named Entity Recognition
inferred← citeshttps://doi.org/10.3390/app112311365openalex-snapshot
Development and Evaluation of an Intelligence and Learning System in Jurisprudence Text Mining in the Field of Competition Defense
inferred← citeshttps://doi.org/10.48084/etasr.10019openalex-snapshot
Exploring Different Annotation Schemes for Single and Consecutive Named Entity Recognition in the Arabic Biomedical Domain using Transformer Models and Contextual Semantic Embeddings
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.