INTRODUCTION Choosing a residency program is a stressful and important decision. Doximity released residency program rankings by specialty in September 2014. This study sought to investigate the impact of those rankings on residency application choices made by fourth year medical students. METHODS A 12-item survey was administered in October 2014 to fourth year medical students at three schoo...

We explore the relationship between official rankings of professional tennis players and rankings computed using a variant of the PageRank algorithm as proposed by Radicchi in 2011. We show Radicchi’s equations follow a natural interpretation of the PageRank algorithm and present up-to-date comparisons of official rankings with PageRankbased rankings for both the Association of Tennis Professio...

Rankings or ratings are popular methods for structuring large information sets in search engines, e-Commerce, e-Learning, etc. But do they produce the right rankings for their users? In this paper, we give an overview of major evaluation approaches for rankings as well as major challenges facing the use and usability of rankings. We point out the importance of an interdisciplinary perspective f...

Cloud computing is an emerging technology that promises competitive advantages, cost savings, enhanced business processes and services, and various other benefits to enterprises. Despite the rapid technological advancement, the adoption of cloud computing is still growing slowly among small and mediumsized enterprises (SMEs). This paper presents a model to support the decisionmaking process, us...

Rankings and ratings are popular methods for structuring large information sets in search engines, e-Commerce, e-Learning, etc. But do they produce the right rankings for their users? In this paper, we give an overview of major evaluation approaches for rankings as well as major challenges facing the use and usability of rankings. We point out the importance of an interdisciplinary perspective ...

In this paper, I present a recursive algorithm that calculates the number of rankings that are consistent with a set of data (i.e. optimal candidates) in the framework of Optimality Theory. The ability to compute this quantity, which I call the r-volume, makes possible a simple and effective Bayesian heuristic in learning – all else equal, choose the candidate preferred by the highest number of...

In many data analysis problems, sequentially ordered (or ranked) data occurs that needs to be understood and compared. Ranking information is essential in applications such as multimedia search where retrieval rankings need to be inspected; alignments of gene sequences in bio-molecular applications; or for a more abstract example, considering the permutations of rows and columns for purpose of ...

Expert search is about finding people rather than documents. The goal is to retrieve a ranked list of candidates with expertise on a given topic. The task is studied in the context of the enterprise track. We describe an approach that compares topic profiles and candidate profiles directly. These profiles are not based on unordered sets of documents, but on ranked lists. This allows us to diffe...

We show that the widely used Kendall tau correlation coefficient, and the related Mallows kernel, are positive definite kernels for permutations. They offer computationally attractive alternatives to more complex kernels on the symmetric group to learn from rankings, or learn to rank. We show how to extend these kernels to partial rankings, multivariate rankings and uncertain rankings. Examples...