Using the full-text content of academic articles to identify and evaluate algorithm entities in the domain of natural language processing.

ABSTRACT: In the era of big data, the advancement, improvement, and application of algorithms in academic research have played an important role in promoting the development of different disciplines. Academic papers in various disciplines, especially computer science, contain a large number of algorithms. Identifying the algorithms from the full-text content of papers can determine popular or classical algorithms in a specific field and help scholars gain a comprehensive understanding of the algorithms and even the field. To this end, this article takes the field of natural language processing (NLP) as an example and identifies algorithms from academic papers in the field. A dictionary of algorithms is constructed by manually annotating the contents of papers, and sentences containing algorithms in

SUBMITTER: Wang Y 

PROVIDER: S-EPMC7548120 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature