A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
The massive data streams observed in network monitoring, data processing and scientific studies are typically too large to store. For many applications over such data, we must ob...
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
A continuous top-k query retrieves the k most preferred objects in a data stream according to a given preference function. These queries are important for a broad spectrum of appl...
Avani Shastri, Di Yang, Elke A. Rundensteiner, Mat...