Connecting firm's web scraped textual content to body of science: Utilizing microsoft academic graph hierarchical topic modeling

Connecting firm's web scraped textual content to body of science: Utilizing microsoft academic graph hierarchical topic modeling

This paper demonstrates a method to transform and link textual information scraped from companies' websites to the scientific body of knowledge. The method illustrates the benefit of Natural Language Processing (NLP) in creating links between established economic classification systems with nov...

Full description

Bibliographic Details
Main Authors: Arash Hajikhani, Lukas Pukelis, Arho Suominen, Sajad Ashouri, Torben Schubert, Ad Notten, Scott W. Cunningham
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:MethodsX
Subjects:
A method for creating a linkage between web scraped company’s websitecontent to scientific literature topical structure
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016122000346

Internet

http://www.sciencedirect.com/science/article/pii/S2215016122000346

Similar Items