We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimen...
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli...
We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into...
Information retrieval algorithms leverage various collection statistics to improve performance. Because these statistics are often computed on a relatively small evaluation corpus...
In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant inf...
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...