TrendFlow: A Machine Learning Framework for Research Trend Analysis

As various research fields continue to evolve, new technologies emerge constantly, making it challenging for scholars to keep up with the latest and most promising research directions. To address this issue, we propose TrendFlow, a framework that leverages machine learning and deep learning techniqu...

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Bibliographic Details
Published inApplied sciences Vol. 13; no. 12; p. 7029
Main Authors Xiang, Tao, Chen, Sufang, Zhang, Yiwei, Zhu, Rui
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2023
Subjects
Algorithms
Clustering
Computational linguistics
Data mining
Datasets
Deep learning
Innovations
keyphrase generation
Language
Language processing
Learning algorithms
Machine learning
Natural language interfaces
Natural language processing
New technology
research trend analysis
Semantics
Trend analysis
Trends
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Summary:As various research fields continue to evolve, new technologies emerge constantly, making it challenging for scholars to keep up with the latest and most promising research directions. To address this issue, we propose TrendFlow, a framework that leverages machine learning and deep learning techniques for analyzing research trends. TrendFlow first searches relevant literature based on user-defined queries, then clusters the searched literature according to the abstracts, and finally generates keyphrases of the abstracts as research trends for each cluster. Our experimental results highlight the superior performance of TrendFlow compared to traditional literature analysis tools. We have released the beta version of TrendFlow on Huggingface.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13127029