An Intra-Class Ranking Metric for Remote Sensing Image Retrieval
Remote Sensing, 2023 With the rapid development of internet technology in recent years, the available remote sensing image data have also been growing rapidly, which has led to an increased demand for remote sensing image retrieval.
Pingping Liu +5 more
doaj +1 more source
Personalization by Relevance Ranking Feedback in Impression-based Retrieval for Multimedia Database [PDF]
Journal of Systemics, Cybernetics and Informatics, 2005 This paper proposes an approach to personalization by relevance `ranking' feedback in impression-based retrieval for a multimedia database. Impression-based retrieval is a kind of ambiguous retrieval, and it enables a database user to find not only a ...
Tsuyoshi TAKAYAMA +2 more
doaj
Investigating the effectiveness of methodological elements in ranking the results based on their relevance and methodological validity [PDF]
Iranian Journal of Information Processing & Management, 2023 Introduction: The goal of evidence-based medicine is helping clinical professionals to obtain relevant and valid information to make appropriate clinical decisions.
Hajar Sotudeh +2 more
doaj +1 more source
Selective Weak Supervision for Neural Information Retrieval [PDF]
The Web Conference, 2020 This paper democratizes neural information retrieval to scenarios where large scale relevance training signals are not available. We revisit the classic IR intuition that anchor-document relations approximate query-document relevance and propose a ...
Kaitao Zhang +3 more
semanticscholar +1 more source
Predicting Emerging Trends on Social Media by Modeling it as Temporal Bipartite Networks
IEEE Access, 2020 The behavior of peoples' request for a post on online social media is a stochastic process that makes post's ranking highly skewed in nature. We mean peoples interest for a post can grow/decay exponentially or linearly.
Asif Khan +6 more
doaj +1 more source
Your relevance feedback is essential: enhancing the learning to rank using the virtual feature based logistic regression. [PDF]
PLoS ONE, 2012 Information retrieval applications have to publish their output in the form of ranked lists. Such a requirement motivates researchers to develop methods that can automatically learn effective ranking models. Many existing methods usually perform analysis
Fei Cai +3 more
doaj +1 more source
Using the quantum probability ranking principle to rank interdependent documents [PDF]
, 2010 A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between ...
A. Khrennikov +13 more
core +2 more sources
IEEE Access, 2021 The rapid growth in the number of scholarly documents on the Web and in other digital platforms makes it challenging for researchers to find research publications most relevant to their information needs.
Shah Khalid +4 more
doaj +1 more source
Ranking structured documents using utility theory in the Bayesian network retrieval model [PDF]
, 2003 In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information ...
F. Crestani +10 more
core +3 more sources
Combination of content analysis and context features for digital photograph retrieval. [PDF]
, 2005 In recent years digital cameras have seen an enormous rise in popularity, leading to a huge increase in the quantity of digital photos being taken. This brings with it the challenge of organising these large collections.
Gurrin, Cathal +3 more
core +1 more source