Results 81 to 90 of about 1,153 (163)

Automating API Documentation with LLMs: A BERTopic Approach

Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering
Developers rely on API documentation, but official sources are often lengthy, complex, or incomplete. Many turn to community-driven forums like Stack Overflow for practical insights. We propose automating the summarization of informal sources, focusing on Android APIs.
openaire   +2 more sources

Real‐Time Anxiety and Depression Detection by Combining Large Language Models and Machine Learning With Explainability Capabilities on a User‐Centric, Engaging Conversational Assistant

Expert Systems, Volume 43, Issue 4, April 2026.
ABSTRACT Mental well‐being is a worldwide priority of health systems. Nevertheless, the diagnosis and recovery rates are still low. This work demonstrates an Artificial Intelligence (AI)‐based, entertainment‐oriented, engaging assistant that can deliver on‐demand, non‐judgmental assessment in an accessible, scalable, and personalised way to people ...
Silvia García‐Méndez, Francisco de Arriba‐Pérez, Julen Beiro‐Suso, Francisco J. González‐Castaño   +3 more
wiley   +1 more source

Artificial Intelligence−Driven Analysis Identifies Anterior Cruciate Ligament Reconstruction, Hip Arthroscopy and Femoroacetabular Impingement Syndrome, and Shoulder Instability as the Most Commonly Published Topics in Arthroscopy

Arthroscopy, Sports Medicine, and Rehabilitation
Purpose: To use advanced topic modeling, specifically the Bidirectional Encoder Representations from Transformers Topic (BERTopic) Model, to analyze research topics in Arthroscopy: The Journal of Arthroscopic and Related Surgery (Arthroscopy).
Henry B.G. Baird, B.S., William Allen, M.D., Mauricio Gallegos, M.D., Cody C. Ashy, M.D., Harris S. Slone, M.D., W. Michael Pullen, M.D.   +5 more
doaj   +1 more source

PEMODELAN TOPIK SARAN MAHASISWA PADA SIMAK UNISMUH MENGGUNAKAN BERTOPIC

This study examines the use of the BERTopic algorithm for topic modeling on student feedback data collected through the SIMAK UNISMUH. The research aims to identify and visualize thematic patterns in student feedback to improve academic services and ...
Wahyuni, Titin, Irhamna Rachman, Fahrim, Indriani, Lis, Yusliana Bakti, Rizki   +3 more
core   +1 more source

Improving Arabic cognitive distortion classification in Twitter using BERTopic [PDF]

, 2022
Social media platforms allow users to share thoughts, experiences, and beliefs. These platforms represent a rich resource for natural language processing techniques to make inferences in the context of cognitive psychology.
Jabri, Riad, Al-Haj, Ali, Alhaj, Fatima, Sharieh, Ahmad   +3 more
core  

Topic information mined by the BERTopic algorithm (N = 17,593).

Topic information mined by the BERTopic algorithm (N = 17,593).
Zhouyi Gu (17972850), Xuan Pan (187031), Zhuoyuan Tang (17972847)   +2 more
core   +1 more source

Integrating topic clustering and sentiment analysis for visitor perception evaluation in historic blocks: insights from the Dadou Road case

Journal of Asian Architecture and Building Engineering
Historic blocks play a crucial role in sustainable urban and rural development by preserving cultural heritage while adapting to contemporary needs. However, visitor perspectives – particularly regarding spatial perceptions and satisfaction – remain ...
Xiao Gu, Xinran Zhang, Zhihua Zhao, Jiaxiu Ping, Gang Du   +4 more
doaj   +1 more source

Exploring the Effects of Pre-Processing Techniques on Topic Modeling of an Arabic News Article Data Set

Applied Sciences
This research investigates the impacts of pre-processing techniques on the effectiveness of topic modeling algorithms for Arabic texts, focusing on a comparison between BERTopic, Latent Dirichlet Allocation (LDA), and Non-Negative Matrix Factorization ...
Haya Alangari, Nahlah Algethami
doaj   +1 more source

Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic

Annals of Computer Science and Information Systems
At the "19th Conference on Computer Science and Intelligence Systems, FedCSIS 2024 (IEEE #61123)" held in Belgrade, September 8–11, 2024, a paper titled Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic, autora Teodora Mihajlov, Milica Ikonić Nešić, Ranka Stanković and Olivera Kitanović, was presented within the session ...
Mihajlov, Teodora, Ikonić Nešić, Milica, Stanković, Ranka, Kitanović, Olivera   +3 more
openaire   +3 more sources

Topic-Keyword data output by the BERTopic model.

This study aims to enhance governmental decision-making by leveraging advanced topic modeling algorithms to analyze public letters on the "People Call Me" online government inquiry platform in Zhejiang Province, China.
Zhouyi Gu (17972850), Xuan Pan (187031), Zhuoyuan Tang (17972847)   +2 more
core   +1 more source