We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio c...
Douglas Turnbull, Luke Barrington, D. Torres, Gert...
Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender sys...
The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
Though children frequently use web search engines to learn, interact, and be entertained, modern web search engines are poorly suited to children's needs, requiring relativel...
Serendipity occurs when one finds an interesting discovery while searching for something else. In digital libraries, recommendation engines are particularly well-suited for seren...