With the advent of online social networks, the trust-based approach to recommendation has emerged which exploits the trust network among users and makes recommendations based on t...
Samaneh Moghaddam, Mohsen Jamali, Martin Ester, Ja...
Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
In this paper we address the issue of continuous keyword queries on multiple textual streams. This line of work represents a significant departure from previous keyword search mod...
Vagelis Hristidis, Oscar Valdivia, Michail Vlachos...
We propose and evaluate a query expansion mechanism that supports searching and browsing in collections of annotated documents. Based on generative language models, our feedback me...
The retrieval performance of content-based image retrieval (CBIR) systems is often disappointingly low, mainly due to the subjectivity of human perception. Relevance feedback (RF)...
Sotirios Chatzis, Anastasios D. Doulamis, Theodora...