A new machine learning model, TweetyBERT, automatically segments and classifies canary vocalizations with expert-level accuracy, offering a scalable platform for neuroscience, providing insights into ...

aInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA bSchool of Medicine, University of Washington, Seattle, WA, USA cGeneral Medicine Service, Department of ...

Google’s first-stage retrieval still runs on word matching, not AI magic. Here’s how to use content scoring tools accordingly.

Abstract: This study examines the emotional and thematic patterns in AI-generated resume feedback using BERT-based topic modeling and transformer-based sentiment analysis under happy and gloomy ...

Experimental results show that the models constructed by the proposed method not only maintain geological semantic consistency and coherence but also accurately characterize the spatial distribution ...

Digital Hostility Toward LGBTQIA+ Research Recruitment on Social Media Using Topic Modeling and Sentiment Analysis of Facebook Comments: Quantitative Content Analysis Study ...

This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experiences as discussed on the social media platform ...

Abstract: This study applies the BERTopic model to analyze an Indonesian news corpus collected in December 2015, identifying and interpreting the primary topics discussed. By comparing the BERTopic ...