A growing number of applications are built on top of search engines and issue complex structured queries. This paper contributes a customisable ranking-based processing of such qu...
In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH...
This paper explores the use of social annotations to improve web search. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their f...
A Reverse k-Nearest-Neighbor (RkNN) query finds the objects that take the query object as one of their k nearest neighbors. In this paper we propose new solutions for evaluating R...
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...