Results 11 to 20 of about 261,614 (261)
A multiple relevance feedback strategy with positive and negative models. [PDF]
PLoS ONE, 2014 A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the
Yunlong Ma, Hongfei Lin
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A multi-dimensional semantic pseudo-relevance feedback framework for information retrieval [PDF]
Scientific ReportsPre-trained models have garnered significant attention in the field of information retrieval, particularly for improving document ranking. Typically, an initial retrieval step using sparse methods such as BM25 is employed to obtain a set of pseudo ...
Min Pan +4 more
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A Query Expansion Method Using Multinomial Naive Bayes
Applied Sciences, 2021 Information retrieval (IR) aims to obtain relevant information according to a certain user need and involves a great diversity of data such as texts, images, or videos. Query expansion techniques, as part of information retrieval (IR), are used to obtain
Sergio Silva +4 more
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Conceptual relevance feedback [PDF]
IEEE International Conference on Systems, Man and Cybernetics, 2005 Contains fulltext : 176141.pdf (Author’s version preprint ) (Open Access)
Grootjen, F.A., Weide, T.P. van der
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Graph Regularized Hierarchical Diffusion Process With Relevance Feedback for Medical Image Retrieval
IEEE Access, 2021 Befitting from the interpretability and the capacity in capturing the underlying manifold structure, diffusion process (DP) has attracted increasing attention in the field of image retrieval.
Liming Xu +4 more
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Journal of Computer Science and Technology, 2022 This article describes an information retrieval system with entity query expansion by relevance feedback. The performance of the system is tested assuming its usage as a support tool for lawyers constructing a legal framework for a case. The objective is
Joel Arnaldo Gimenez Catacora +2 more
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Positional relevance model for pseudo-relevance feedback [PDF]
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2010 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 query expansion, which is not optimal as a document may cover several different topics and thus contain much irrelevant information.
Yuanhua Lv, ChengXiang Zhai
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Salton and Buckley’s Landmark Research in Experimental Text Information Retrieval
Evidence Based Library and Information Practice, 2011 Objectives – To compare the performance of the vector space model and the probabilistic weighting model of relevance feedback for the overall purpose of determining the most useful relevance feedback procedures.
Christine F. Marton
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Implicit Adaptation Is Modulated by the Relevance of Feedback [PDF]
Journal of Cognitive Neuroscience, 2022 Abstract Given that informative and relevant feedback in the real world is often intertwined with distracting and irrelevant feedback, we asked how the relevancy of visual feedback impacts implicit sensorimotor adaptation. To tackle this question, we presented multiple cursors as visual feedback in a center-out reaching task and ...
Darius E. Parvin +5 more
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Relevance Feedback in CBIR [PDF]
, 2002 A new focus in content-based image retrieval (CBIR) research is applying relevance feedback originally developed for text document retrieval, to improve the retrieval performance. This effort tries to bridge the gap between low-level image features and high-level semantic contents of images as this gap is the bottleneck of CBIR.
HongJiang Zhang, Zhong Su
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