Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets...
Alexandra Rostin, Oliver Albrecht, Jana Bauckmann,...
Many systems such as Tukwila and YFilter combine automaton and algebra techniques to process queries over tokenized XML streams. Typically in this architecture, an automaton is fi...
We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as ...
Gleb Skobeltsyn, Toan Luu, Karl Aberer, Martin Raj...