Automatic thematic classification of documents based on vocabularies and use frequencies. The case of scientific dissemination articles
DOI:
https://doi.org/10.3989/redc.2023.3.1996Keywords:
Document classification, thematic classification, algorithm, vocabularies, lexical frequencies, science disseminationAbstract
It is often necessary to classify documents by assigning them a theme or topic from a series of predefined options. This work is usually done manually, by reading the document by a specialist. This manual process is tedious, requires time and resources, and is prone to bias and preferences of each specialist.
As an alternative, this article presents an automatic thematic classification system, capable of classifying hundreds of documents in a few seconds, highly parameterized, and that does not require the specialists intervention. The system is based on predefined thematic vocabularies and frequencies of use of lexical forms, and assigns one or more priority topics to each document. The suggested approach has been developed and tested in the context of scientific dissemination articles in the Spanish language.
Using this approach, it is possible to systematically classify large amounts of documents by topic, using fewer resources than doing it manually, and avoiding unknown biases. The approach has shown to be as effective as other proposals, but requires less computational resources.
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