Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the...
In this project (VIRSI) we investigate the promising contentbased retrieval paradigm known as interactive search or relevance feedback, and aim to extend it through the use of syn...
Bart Thomee, Mark J. Huiskes, Erwin M. Bakker, Mic...
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
based on an abstract concept of quiescence. In the following we sketch this and a related model, describe the design of our experiments, and present the results of our simulation s...