The changing landscape of text mining - a review of approaches for ecology and evolution

Опубликована: Фев. 20, 2024

In ecology and evolutionary biology, synthesis modelling of data from published literature is a common practice for generating insight testing theories across systems. However, the tasks searching, screening, extracting are often arduous. Researchers may manually process hundreds to thousands articles systematic reviews, meta-analyses, compiling synthetic datasets. As relevant expand tens or thousands, computer-based approaches can increase efficiency dramatically improve transparency reproducibility literature-based research. Methods available text mining rapidly changing due developments in machine learning-based language models. Here we review growing landscape approaches, mapping them onto three broad paradigms (Frequency-based Traditional Natural Language Processing, Deep models). This serves as an entry point learn foundational cutting edge concepts, vocabularies, methods, foster better integration these tools into ecological We discuss texts, training data, developing custom models, interacting with Large Models, present challenges possible solutions implementing methods evolution.

Язык: Английский

In situ soil imaging, a tool for monitoring the hourly to monthly temporal dynamics of soil biota

Biology and Fertility of Soils, Год журнала: 2024, Номер 60(8), С. 1055 - 1071

Опубликована: Авг. 6, 2024

Язык: Английский