We introduce and validate bootstrap techniques to compute confidence intervals that quantify the effect of test-collection variability on average precision (AP) and mean average...
Many traditional information retrieval models, such as BM25 and language modeling, give good retrieval effectiveness, but can be difficult to implement efficiently. Recently, docum...
Abstract. We show that several previously proposed passage-based document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use lan...
Image annotations allow users to access a large image database with textual queries. There have been several studies on automatic image annotation utilizing machine learning techn...
In relevance feedback, active learning is often used to alleviate the burden of labeling by selecting only the most informative data. Traditional data selection strategies often c...