Search results for "RELEVANCE"
showing 10 items of 500 documents
Special Issue 'Spin Crossover (SCO) Research'
2016
This special issue, entitled “Spin Crossover (SCO) Research”, illustrates the current relevance of a focused topic, which is inturn highly versatile. Indeed, the collection of papers presented constitutes a sampler that shows the topical importance of this area by attracting the interest of many top researchers and how it is approached under a multidisciplinary perspective.[...]
A naive relevance feedback model for content-based image retrieval using multiple similarity measures
2010
This paper presents a novel probabilistic framework to process multiple sample queries in content based image retrieval (CBIR). This framework is independent from the underlying distance or (dis)similarity measures which support the retrieval system, and only assumes mutual independence among their outcomes. The proposed framework gives rise to a relevance feedback mechanism in which positive and negative data are combined in order to optimally retrieve images according to the available information. A particular setting in which users interactively supply feedback and iteratively retrieve images is set both to model the system and to perform some objective performance measures. Several repo…
Bayesian Metanetwork for Context-Sensitive Feature Relevance
2006
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of appropriate conditional dependency. However, depending on task and context, many attributes of the model might not be relevant. If a network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on a “relevance” of the predictive attributes towards tar…
A novel Bayesian framework for relevance feedback in image content-based retrieval systems
2006
This paper presents a new algorithm for image retrieval in content-based image retrieval systems. The objective of these systems is to get the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The main problem in obtaining a robust and effective retrieval is the gap between the low level descriptors that can be automatically extracted from the images and the user intention. The algorithm proposed here to address this problem is based on the modeling of user preferences as a probability distribution on the image space. Following a Bayesian methodology, this distribution is the pr…
An improved distance-based relevance feedback strategy for image retrieval
2013
Most CBIR (content based image retrieval) systems use relevance feedback as a mechanism to improve retrieval results. NN (nearest neighbor) approaches provide an efficient method to compute relevance scores, by using estimated densities of relevant and non-relevant samples in a particular feature space. In this paper, particularities of the CBIR problem are exploited to propose an improved relevance feedback algorithm based on the NN approach. The resulting method has been tested in a number of different situations and compared to the standard NN approach and other existing relevance feedback mechanisms. Experimental results evidence significant improvements in most cases.
Interactive Image Retrieval Using Smoothed Nearest Neighbor Estimates
2010
Relevance feedback has been adopted by most recent Content Based Image Retrieval systems to reduce the semantic gap that exists between the subjective similarity among images and the similarity measures computed in a given feature space. Distance-based relevance feedback using nearest neighbors has been recently presented as a good tradeoff between simplicity and performance. In this paper, we analyse some shortages of this technique and propose alternatives that help improving the efficiency of the method in terms of the retrieval precision achieved. The resulting method has been evaluated on several repositories which use different feature sets. The results have been compared to those obt…
Research opportunities in performance measurement in public utilities regulation
2015
Purpose – The purpose of this paper is to propose a method to choose a set of scientific articles about performance measurement in public utilities regulation. The method is designed to identify references with high academic relevance in databases accessed via the internet, and, through these articles, to perform a mapping of these publications and conduct a systemic analysis. Design/methodology/approach – The study is characterized as exploratory and descriptive with a qualitative and quantitative approach. Incorporates an inductive logic, and draws on primary and secondary data sources. The research involves the application of a technical procedure for selection and study of selected art…
Revealing the unique features of each individual’s muscle activation signatures
2020
AbstractThere is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear Support Vector Machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision making by the machine learning classification model, a Layer-wise Relevance Propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance scores for each i…
Multiperspective Evaluation of Reference Models – Towards a Framework
2003
Within the information systems field, reference models have been known for many years. Despite the relevance of reference model quality, little research has been done on their systematic evaluation. Based on an analysis of prior work on reference model quality, we propose a framework for the multiperspective evaluation of reference models. The framework comprises 15 perspectives. Each perspective is discussed with respect to its strengths and limitations. As well, we provide examples of the types of research that have already been undertaken on each perspective.
A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …
2013
Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…