dataset · Figshare · 2024

Topic Extraction Dataset

Bitaraf, Ehsan

Cited by 0Open access

Abstract

In this dataset, a total of 9691 articles within the medical domain were collected for analysis. Topic extraction was conducted utilizing two distinct methodologies: Textrank and LLM. These approaches were applied in conjunction with the keywords present in the articles, forming the dataset for analysis. The dataset encompasses various fields such as article title, publication year, PMID, keyword listings, topics derived through the Textrank algorithm, and topics identified through LLM.

Cite this paper

APA 7

Bitaraf, E. (2024). Topic Extraction Dataset. Figshare. https://doi.org/10.6084/m9.figshare.25533532.v1

MLA 9

Bitaraf, Ehsan. “Topic Extraction Dataset.” Figshare, 2024, https://doi.org/10.6084/m9.figshare.25533532.v1.

Chicago

Bitaraf, Ehsan. 2024. “Topic Extraction Dataset.” Figshare. https://doi.org/10.6084/m9.figshare.25533532.v1.

Harvard

Bitaraf, E. (2024) ‘Topic Extraction Dataset’, Figshare. Available at: https://doi.org/10.6084/m9.figshare.25533532.v1.

BibTeX

@misc{bitaraf2024topic,
  title = {{Topic Extraction Dataset}},
  author = {Bitaraf, Ehsan},
  journal = {Figshare},
  year = {2024},
  doi = {10.6084/m9.figshare.25533532.v1}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.