Work

Spectrep: A software for spectral representation of text content

Year: 2024

Type: software-paper

Abstract: Sectrep (Spectral Representation) implements a text representation framework for obtaining a multi-view representation that consolidates lexical, syntactic, and semantic features by structuring a workflow with popular text processing tools such as NTLK, Gensim, and Self-Organizing Maps. This framework is intended to be used in text pre-processing for its application in more robust machine learning applications. This software is open-source and implemented in Python. It has been successfully tested with several tasks to prove its functionality.

Source: SoftwareX

DOI: 10.1016/j.softx.2024.101849

Authors: Melesio Crespo-Sanchez, Ivan Lopez-Arevalo, Edwin Aldana-Bobadilla, Helena Gomez-Adorno, Jose Luis Gonzalez-Compean

Institutions: Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Secretaría de Ciencia, Humanidades, Tecnología e Innovación, Universidad Nacional Autónoma de México

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $970

Funders: Consejo Nacional de Ciencia y Tecnología, Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México