Modeling Score Distributions

TL;DR: This work proposes a resource selection method based on document score distribution models that supports estimation of uncertainty of produced source scores and results in a novel risk-aware resource selection technique.

TL;DR: CaRBS analyses are presented here to illustrate that data mining can manage the presence of missing values in a much more effective manner than the more inhibitory traditional strategies.

TL;DR: It is shown that reference values calculated by the similarity‐oriented approach are considerably better at predicting the assessed articles' citation count compared to the reference values given by the journal‐set approach, thus significantly reducing the variability in the observed citation distribution that stems from the variabilityIn the articles' addressed subject matter.

TL;DR: Overall, this thesis concludes that distributional assumptions can be replaced with an effective, efficient and principled method for determining the "true" distribution and that using the " true" distribution can lead to improved retrieval performance.

TL;DR: This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory, and will guide practitioners to updated literature, new applications, and on-line software.

TL;DR: In this article, the authors present a rigorous and complete textbook for a first course on information retrieval from the computer science (as opposed to a user-centred) perspective, which provides an up-to-date student oriented treatment of the subject.

TL;DR: This book is the first comprehensive introduction to Support Vector Machines, a new generation learning system based on recent advances in statistical learning theory, and introduces Bayesian analysis of learning and relates SVMs to Gaussian Processes and other kernel based learning methods.

TL;DR: In this paper, the authors present a survey of the main domains of attraction and norming constants in point processes and point processes, and their relationship with multivariate extremity processes.