Topic tracking is an important task of Topic Detection and Tracking (TDT). Its purpose is to detect stories, from a stream of news, related to known topics. Each topic is “known...
Topic tracking is complicated when the stories in the stream occur in multiple languages. Typically, researchers have trained only English topic models because the training storie...
Leah S. Larkey, Fangfang Feng, Margaret E. Connell...
Detecting and tracking latent factors from temporal data is an important task. Most existing algorithms for latent topic detection such as Nonnegative Matrix Factorization (NMF) h...
Bin Cao, Dou Shen, Jian-Tao Sun, Xuanhui Wang, Qia...
Algorithms that enable the process of automatically mining distinct topics in document collections have become increasingly important due to their applications in many fields and ...
Videos from distributed sources (e.g., broadcasts, podcasts, blogs, etc.) have grown exponentially. Topic threading is very useful for organizing such large-volume information sou...