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...
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extend in various real-life applications. ...