Impact of interaction strategies on user relevance feedback
User Relevance Feedback (URF) is a class of interactive learning methods that rely on the
interaction between a human user and a system to analyze a media collection. To improve …
interaction between a human user and a system to analyze a media collection. To improve …
Benchmarking image retrieval diversification techniques for social media
Image retrieval has been an active research domain for over 30 years and historically it has
focused primarily on precision as an evaluation criterion. Similar to text retrieval, where the …
focused primarily on precision as an evaluation criterion. Similar to text retrieval, where the …
Exquisitor at the video browser showdown 2021: relationships between semantic classifiers
Exquisitor is a scalable media exploration system based on interactive learning, which first
took part in VBS in 2020. This paper presents an extension to Exquisitor, which supports …
took part in VBS in 2020. This paper presents an extension to Exquisitor, which supports …
Boosting Diversity in Visual Search with Pareto Non-Dominated Re-Ranking
The field of visual search has gained significant attention recently, particularly in the context
of web search engines and e-commerce product search platforms. However, the abundance …
of web search engines and e-commerce product search platforms. However, the abundance …
Result diversification in image retrieval based on semantic distance
User requirements for result diversification in image retrieval have been increasing with the
explosion of image resources. Result diversification requires that image retrieval systems …
explosion of image resources. Result diversification requires that image retrieval systems …
Block-based pseudo-relevance feedback for image retrieval
WC Lin - Journal of Experimental & Theoretical Artificial …, 2022 - Taylor & Francis
Pseudo-relevance feedback (PRF) is a relevance feedback (RF) technique for information
retrieval that treats the top k retrieved images as relevance feedback. PRF is used to avoid …
retrieval that treats the top k retrieved images as relevance feedback. PRF is used to avoid …
Hypergraph learning with collaborative representation for image search reranking
Image search reranking has received considerable attention in recent years. It aims at
refining the text-based image search results by boosting the rank of relevant images …
refining the text-based image search results by boosting the rank of relevant images …
[PDF][PDF] LAPI@ 2016 Retrieving Diverse Social Images Task: A Pseudo-Relevance Feedback Diversification Perspective.
In this paper we present the results achieved during the 2016 Media-Eval Retrieving Diverse
Social Images Task, using an approach based on pseudo-relevance feedback, in which …
Social Images Task, using an approach based on pseudo-relevance feedback, in which …
Supervised learning methods for diversification of image search results
B Goynuk, IS Altingovde - … Retrieval: 42nd European Conference on IR …, 2020 - Springer
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Hypergraph-based image search reranking with elastic net regularized regression
Image search reranking is emerging as an effective technique to refine the text-based image
search results using visual information. In this paper, we introduce a novel hypergraph …
search results using visual information. In this paper, we introduce a novel hypergraph …