Scientists typically need to take a large volume of information into account in order to deal with re-occurring tasks such as inspecting proceedings, finding related work, or revi...
Algirdas Avizienis, Gintare Grigonyte, Johann Hall...
Traditional content-based image retrieval (CBIR) systems often fail to meet a user's need due to the `semantic gap' between the extracted features of the systems and the...
The proliferation of knowledge-sharing communities and the advances in information extraction have enabled the construction of large knowledge bases using the RDF data model to re...
Nicoleta Preda, Gjergji Kasneci, Fabian M. Suchane...
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...
Independent from specific application domains, similar requirements can be identified regarding information needs during daily work. For coping with generality on the one hand an...