We present an approach to information retrieval based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This conte...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
We present iClusterDL, a self-organising overlay network that supports information retrieval and filtering functionality in a digital library environment. iClusterDL is able to han...
Paraskevi Raftopoulou, Euripides G. M. Petrakis, C...
Document fields, such as the title or the headings of a document, offer a way to consider the structure of documents for retrieval. Most of the proposed approaches in the literatu...
In this paper we demonstrate that speech recognition can be effectively applied to information retrieval (IR) applications. Our system exploits the fact that the intended words of...