This paper details our experiments carried out at TREC 2008 Relevance Feedback Track. We focused on the analysis of feedback documents, both relevant and non-relevant, to explore more useful information to improve retrieval performance. In our experiments, local co-occurrence model and a Rocchio formula were used to select good expansion terms. Five runs were submitted. These runs used different amount of relevance info for analysis.
We describe the participation of the University of Amsterdam’s ILPS group in the relevance feedback ...
This document contains a description of experiments for the 2008 Relevance Feedback track. We experi...
We describe the participation of the University of Amsterdam’s Intelligent Systems Lab in the releva...
The main goals of our participation in the Relevance feedback track at TREC 2008 were the following....
Abstract. Our group has participated into Relevance Feedback (RF) Track in TREC2008. In our experime...
Relevance feedback is the retrieval task where the system is given not only an information need, but...
User relevance feedback is usually utilized by Web systems to interpret user information needs and ...
The purpose of this paper is to examine how various types of TREC data can be used to better underst...
Relevance feedback in text retrieval systems is a process where a user gives explicit feedback on an...
Abstract. We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 ...
In TREC-6, we participated in both the automatic and manual tracks for category A. For the automatic...
This document contains a description of experiments for the 2008 Relevance Feedback track. We experi...
For TREC-5, we enhanced our existing prototype that implements relevance ranking using the AT&T ...
Traditional relevance feedback technique could help improve retrieval performance. It usually utiliz...
We describe the participation of the University of Amsterdam's ILPS group in the blog, enterprise an...
We describe the participation of the University of Amsterdam’s ILPS group in the relevance feedback ...
This document contains a description of experiments for the 2008 Relevance Feedback track. We experi...
We describe the participation of the University of Amsterdam’s Intelligent Systems Lab in the releva...
The main goals of our participation in the Relevance feedback track at TREC 2008 were the following....
Abstract. Our group has participated into Relevance Feedback (RF) Track in TREC2008. In our experime...
Relevance feedback is the retrieval task where the system is given not only an information need, but...
User relevance feedback is usually utilized by Web systems to interpret user information needs and ...
The purpose of this paper is to examine how various types of TREC data can be used to better underst...
Relevance feedback in text retrieval systems is a process where a user gives explicit feedback on an...
Abstract. We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 ...
In TREC-6, we participated in both the automatic and manual tracks for category A. For the automatic...
This document contains a description of experiments for the 2008 Relevance Feedback track. We experi...
For TREC-5, we enhanced our existing prototype that implements relevance ranking using the AT&T ...
Traditional relevance feedback technique could help improve retrieval performance. It usually utiliz...
We describe the participation of the University of Amsterdam's ILPS group in the blog, enterprise an...
We describe the participation of the University of Amsterdam’s ILPS group in the relevance feedback ...
This document contains a description of experiments for the 2008 Relevance Feedback track. We experi...
We describe the participation of the University of Amsterdam’s Intelligent Systems Lab in the releva...