Relevance feedback is a powerful technique for content-based image retrieval. Many parameter estimation approaches have been proposed for relevance feedback. However, most of them ...
This paper is to investigate the group behavior patterns of search activities based on Web search history data, i.e., clickthrough data, to boost search performance. We propose a ...
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...
Users’ cross-lingual queries to a digital library system might be short and not included in a common translation dictionary (unknown terms). In this paper, we investigate the fe...
In this paper, we propose a multimodal Web image retrieval technique based on multi-graph enabled active learning. The main goal is to leverage the heterogeneous data on the Web t...