Results 161 to 170 of about 11,682 (203)
Some of the next articles are maybe not open access.
Investigating the suboptimality and instability of pseudo-relevance feedback
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2010Although Pseudo-Relevance Feedback (PRF) techniques improve average retrieval performance at the price of high variance, not much is known about their optimality and the reasons for their instability. In this work, we study more than 800 topics from several test collections including the TREC Robust Track and show that PRF techniques are highly ...
Raghavendra Udupa, Abhijit Bhole
openaire +1 more source
Pseudo relevance feedback based on majority voting mechanism
International Journal of Web Science, 2017 Bachir Boucheham
exaly +2 more sources
An incremental approach to efficient pseudo-relevance feedback
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, 2013Pseudo-relevance feedback is an important strategy to improve search accuracy. It is often implemented as a two-round retrieval process: the first round is to retrieve an initial set of documents relevant to an original query, and the second round is to retrieve final retrieval results using the original query expanded with terms selected from the ...
Hao Wu 0036, Hui Fang 0001
openaire +1 more source
A Theoretical Analysis of Pseudo-Relevance Feedback Models
Proceedings of the 2013 Conference on the Theory of Information Retrieval, 2013Our goal in this study is to compare several widely used pseudo-relevance feedback (PRF) models and understand what explains their respective behavior. To do so, we first analyze how different PRF models behave through the characteristics of the terms they select and through their performance on two widely used test collections.
Stéphane Clinchant, Éric Gaussier
openaire +1 more source
Predicting document effectiveness in pseudo relevance feedback
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011Pseudo relevance feedback (PRF) is one of effective practices in Information Retrieval. In particular, PRF via the relevance model (RM) has been widely used due to the theoretical soundness and effectiveness. In a PRF scenario, an underlying relevance model is inferred by combining language models of the top retrieved documents where the contribution ...
Mostafa Keikha +3 more
openaire +1 more source
Pseudo-Relevance Feedback Based on Matrix Factorization
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 2016In information retrieval, pseudo-relevance feedback (PRF) refers to a strategy for updating the query model using the top retrieved documents. PRF has been proven to be highly effective in improving the retrieval performance. In this paper, we look at the PRF task as a recommendation problem: the goal is to recommend a number of terms for a given query
Hamed Zamani +3 more
openaire +1 more source
Term Proximity Constraints for Pseudo-Relevance Feedback
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017Pseudo-relevance feedback (PRF) refers to a query expansion strategy based on top-retrieved documents, which has been shown to be highly effective in many retrieval models. Previous work has introduced a set of constraints (axioms) that should be satisfied by any PRF model.
Ali Montazeralghaem +2 more
openaire +1 more source
Estimation and use of uncertainty in pseudo-relevance feedback
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007Existing pseudo-relevance feedback methods typically perform averaging over the top-retrieved documents, but ignore an important statistical dimension: the risk or variance associated with either the individual document models, or their combination. Treating the baseline feedback method as a black box, and the output feedback model as a random variable,
Kevyn Collins-Thompson, Jamie Callan
openaire +1 more source
Block-based pseudo-relevance feedback for image retrieval
Journal of Experimental & Theoretical Artificial Intelligence, 2021Pseudo-relevance feedback (PRF) is a relevance feedback (RF) technique for information retrieval that treats the top k retrieved images as relevance feedback.
openaire +1 more source
Pseudo-Relevance Feedback Based on mRMR Criteria
2010Pseudo-relevance feedback has shown to be an effective method in many information retrieval tasks. Various criteria have been proposed to rank terms extracted from the top ranked document of the initial retrieval results. However, most existing methods extract terms individually and do not consider the impacts of relationships among terms and their ...
Yuanbin Wu +3 more
openaire +1 more source