Results 231 to 240 of about 2,490,590 (283)
Some of the next articles are maybe not open access.
Pseudo relevance feedback optimization
Information Retrieval Journal, 2021We propose a method for automatic optimization of pseudo relevance feedback (PRF) in information retrieval. Based on the conjecture that the initial query’s contribution to the final query may not be necessary once a good model is built from pseudo relevant documents, we set out to optimize per query only the number of top-retrieved documents to be ...
Avi Arampatzis +2 more
openaire +3 more sources
Relevance feedback in Surfimage
Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201), 2002Relevance feedback is one of the strong components of Surfimage, the INRIA content-based image retrieval system. Relevance feedback is about learning from user interaction, and is useful in tasks like query refinement and multiple queries. We present two relevance feedback techniques currently implemented in Surfimage.
Christophe Meilhac +2 more
openaire +1 more source
Collaborative pseudo-relevance feedback
Expert Systems With Applications, 2013Pseudo-relevance feedback (PRF) is a technique commonly used in the field of information retrieval. The performance of PRF is heavily dependent upon parameter values. When relevance judgements are unavailable, these parameters are difficult to set. In the following paper, we introduce a novel approach to PRF inspired by collaborative filtering (CF). We
Jianxun Liu
exaly +3 more sources
Proceedings of the 1st international conference on Information interaction in context - IIiX, 2006
We present results of a preliminary study of a pile-based information retrieval interface that supports contextual relevance feedback. We designed two interfaces based on the pile metaphor, one which supported contextual relevance feedback and the other which did not, and conducted a within-subjects laboratory evaluation with 24 subjects.
David J. Harper, Diane Kelly 0001
openaire +2 more sources
We present results of a preliminary study of a pile-based information retrieval interface that supports contextual relevance feedback. We designed two interfaces based on the pile metaphor, one which supported contextual relevance feedback and the other which did not, and conducted a within-subjects laboratory evaluation with 24 subjects.
David J. Harper, Diane Kelly 0001
openaire +2 more sources
ACM Transactions on Information Systems, 2019
Document retrieval methods that utilize relevance feedback often induce a single query model from the set of feedback documents, specifically, the relevant documents. We empirically show that for a few state-of-the-art query-model induction methods, retrieval performance can be significantly improved by constructing the query model from a subset of the
Oren Kurland, Fiana Raiber
exaly +2 more sources
Document retrieval methods that utilize relevance feedback often induce a single query model from the set of feedback documents, specifically, the relevant documents. We empirically show that for a few state-of-the-art query-model induction methods, retrieval performance can be significantly improved by constructing the query model from a subset of the
Oren Kurland, Fiana Raiber
exaly +2 more sources
Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '92, 1992
Researchers have found relevance feedback to be effective in interactive information retrieval, although few formal user experiments have been made. In order to run a user experiment on a large document collection, experiments were performed at NIST to complete some of the missing links found in using the probabilistic retrieval model.
openaire +2 more sources
Researchers have found relevance feedback to be effective in interactive information retrieval, although few formal user experiments have been made. In order to run a user experiment on a large document collection, experiments were performed at NIST to complete some of the missing links found in using the probabilistic retrieval model.
openaire +2 more sources
Image retrieval with relevance feedback
Proceedings 29th Applied Imagery Pattern Recognition Workshop, 2002The proposed system for image retrieval using multidimensional features (IRMF) characterises and matches image content in a high dimensional feature space of colour, texture and shape dimensions. By including the entire pyramid of low-, medium-, and high-level primitives, the semantics of image content at different feature levels can be represented and
Li Fang, Yew-Hock Ang
openaire +2 more sources
Relevance Feedback with Brain Signals
ACM Transactions on Information SystemsThe Relevance Feedback (RF) process relies on accurate and real-time relevance estimation of feedback documents to improve retrieval performance. Since collecting explicit relevance annotations imposes an extra burden on the user, extensive studies have explored using pseudo-relevance signals and implicit feedback signals as substitutes.
Xiaohui Xie, Qingyao Ai, Zhihong Wang
exaly +4 more sources
Incremental relevance feedback
Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '92, 1992Although relevance feedback techniques have been investigated for more than 20 years, hardly any of these techniques has been implemented in a commercial full-text document retrieval system. In addition to pure performance problems, this is due to the fact that the application of relevance feedback techniques increases the complexity of the user ...
openaire +2 more sources
On bias problem in relevance feedback
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011Relevance feedback is an effective approach to improve retrieval quality over the initial query. Typical relevance feedback methods usually select top-ranked documents for relevance judgments, then query expansion or model updating are carried out based on the feedback documents.
Qianli Xing 0001 +2 more
openaire +1 more source