Recent Trend
Recent research highlights a surge in applying artificial intelligence, particularly deep learning models like transformers and graph neural networks, to analyze diverse data types, including conversations, satellite communications, time series, and images. Current efforts focus on improving model interpretability, addressing biases, and enhancing the efficiency of algorithms for tasks such as forecasting, trend identification, and knowledge extraction. This work is significant for advancing various fields, from improving business decision-making through conversation analysis to optimizing resource allocation in satellite communication and enhancing personalized education through data mining.
Papers
Semi-automated extraction of research topics and trends from NCI funding in radiological sciences from 2000-2020
Mark Nguyen, Peter Beidler, Joseph Tsai, August Anderson, Daniel Chen, Paul Kinahan, John Kang
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions
Nadav Cohen, Itzik Klein
Recent Developments in Recommender Systems: A Survey
Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria
Recent Trends in Unsupervised Summarization
Mohammad Khosravani, Amine Trabelsi
Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature
Ana Cláudia Akemi Matsuki de Faria, Felype de Castro Bastos, José Victor Nogueira Alves da Silva, Vitor Lopes Fabris, Valeska de Sousa Uchoa, Décio Gonçalves de Aguiar Neto, Claudio Filipi Goncalves dos Santos