This is the official repo for the paper "TrendFlow: A Machine Learning Framework for Research Trend Analysis".
See the code
TrendFlow is an advanced framework that uses deep learning techniques to analyze research trends. This powerful framework offers a wide range of analytical capabilities, including literature clustering, trend generation, and trend summarization. With TrendFlow, you can gain insights into emerging research topics and stay up-to-date on the latest advancements in your field.
@Article{app13127029,
AUTHOR = {Xiang, Tao and Chen, Sufang and Zhang, Yiwei and Zhu, Rui},
TITLE = {TrendFlow: A Machine Learning Framework for Research Trend Analysis},
JOURNAL = {Applied Sciences},
VOLUME = {13},
YEAR = {2023},
NUMBER = {12},
ARTICLE-NUMBER = {7029},
URL = {https://www.mdpi.com/2076-3417/13/12/7029},
ISSN = {2076-3417},
ABSTRACT = {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.},
DOI = {10.3390/app13127029}
}
This is the official repo for the paper "TrendFlow: A Machine Learning Framework for Research Trend Analysis".
See the code
TrendFlow is an advanced framework that uses deep learning techniques to analyze research trends. This powerful framework offers a wide range of analytical capabilities, including literature clustering, trend generation, and trend summarization. With TrendFlow, you can gain insights into emerging research topics and stay up-to-date on the latest advancements in your field.
@Article{app13127029,
AUTHOR = {Xiang, Tao and Chen, Sufang and Zhang, Yiwei and Zhu, Rui},
TITLE = {TrendFlow: A Machine Learning Framework for Research Trend Analysis},
JOURNAL = {Applied Sciences},
VOLUME = {13},
YEAR = {2023},
NUMBER = {12},
ARTICLE-NUMBER = {7029},
URL = {https://www.mdpi.com/2076-3417/13/12/7029},
ISSN = {2076-3417},
ABSTRACT = {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.},
DOI = {10.3390/app13127029}
}