mlsanityData to 14 Oct 2026

Topical Classification of Food Safety Publications with a Knowledge Base

arXiv 2201.00374 ↗First posted 2 Jan 2022cs.CLcited by 1

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Abstract (arXiv)

The vast body of scientific publications presents an increasing challenge of finding those that are relevant to a given research question, and making informed decisions on their basis. This becomes extremely difficult without the use of automated tools. Here, one possible area for improvement is automatic classification of publication abstracts according to their topic. This work introduces a novel, knowledge base-oriented publication classifier. The proposed method focuses on achieving scalability and easy adaptability to other domains. Classification speed and accuracy are shown to be satisfactory, in the very demanding field of food safety. Further development and evaluation of the method is needed, as the proposed approach shows much potential.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 5 of its 30 references that are in the map. First posted on arXiv 2 Jan 2022.

Builds on

5 of 30 references.

References · 5

  1. 2019ScispaCy: Fast and Robust Models for Biomedical Natural Language Processingcited by 244
  2. 2021The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articlescited by 16
  3. 2019Extracting UMLS Concepts from Medical Text Using General and Domain-Specific Deep Learning Modelscited by 3
  4. 2020Medical Knowledge-enriched Textual Entailment Frameworkcited by 3
  5. 2014Foundations of an Alternative Approach to Reification in RDFcited by 2

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Citing papers per year: 2022: 1.

1 paper.