Data and Knowledge Organization for Natural Language Processing: Searching and Identifying Better Arrangements of Texts Based on Multimodal Information Architecture

George Hideyuki Kuroki Júnior and Cláudio Gottschalg-Duque

SAGE Open, 2024, vol. 14, issue 1, 21582440231177042

Abstract: Processing texts of multiple knowledge areas is a hard task. This article presents an Information Science contribution to natural language processing based on artificial neural networks through data arrangement. An extended concept of Information architecture was used, aggregating a multimodal view of organizing data. The Multimodal Information Architecture definition served as foundations for a five-step procedure to design, analyze and transform data used for artificial neural networks training and learning methods, complementing gaps identified by authors focused on Computer Science implementations. The proposal was validated with three datasets formed by texts coming from 16 knowledge areas. Results obtained through the usage of pre-processed data and raw data where compared. In each of the three datasets, the method identified arrangements which led to better and worst results, separating which corpus samples are more susceptible for knowledge extraction.

Keywords: data arrangement; Information Science; Information Architecture; Information Treatment; artificial intelligence; natural language processing (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/21582440231177042 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:1:p:21582440231177042

DOI: 10.1177/21582440231177042

Access Statistics for this article

More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().