Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition

Nadeesha Perera; Thi Thuy Linh Nguyen; Matthias Dehmer; Frank Emmert-Streib

doi:10.3390/make4010012

Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition

Nadeesha Perera, Thi Thuy Linh Nguyen, Matthias Dehmer, Frank Emmert-Streib

Computing Sciences

Research output: Contribution to journal › Article › Scientific › peer-review

11 Citations (Scopus)

40 Downloads (Pure)

Original language	English
Pages (from-to)	254-275
Number of pages	22
Journal	Machine Learning and Knowledge Extraction
Volume	4
Issue number	1
DOIs	https://doi.org/10.3390/make4010012
Publication status	Published - Mar 2022
Publication type	A1 Journal article-refereed

Keywords

Biomedical named-entity recognition
Conditional random fields
Deep language models
Dictionary modeling
Food and dietary constituents extraction
Machine learning
Nutrition-entity extraction
Phytochemical extraction

Publication forum classification

Publication forum level 1

Access to Document

10.3390/make4010012Licence: CC BY

make-04-00012-v2Final published version, 1.12 MBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202301251754Licence: CC BY

Cite this

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title = "Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition",

keywords = "Biomedical named-entity recognition, Conditional random fields, Deep language models, Dictionary modeling, Food and dietary constituents extraction, Machine learning, Nutrition-entity extraction, Phytochemical extraction",

author = "Nadeesha Perera and Nguyen, {Thi Thuy Linh} and Matthias Dehmer and Frank Emmert-Streib",

year = "2022",

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AU - Emmert-Streib, Frank

PY - 2022/3

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KW - Biomedical named-entity recognition

KW - Conditional random fields

KW - Deep language models

KW - Dictionary modeling

KW - Food and dietary constituents extraction

KW - Machine learning

KW - Nutrition-entity extraction

KW - Phytochemical extraction

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DO - 10.3390/make4010012

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