Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
In an environment of distributed text collections, the first step in the information retrieval process is to identify which of all available collections are more relevant to a giv...
In this paper we review the evaluation of relevance feedback methods for content-based image retrieval systems. We start out by presenting an overview of current common practice, ...
Relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. This work extends the existing framework of image retrieval with relevan...
Euripides G. M. Petrakis, Klaydios Kontis, Epimeni...