In this paper, we report on the creation of a publicly available, common evaluation
framework for image and video visual interestingness prediction. We propose a robust data …

We conducted a systematic review of 840 SIGIR full papers and 215 TOIS papers published
between 2006 and 2015. The original objective of the study was to identify IR effectiveness …

Statistical significance testing is widely accepted as a means to assess how well a difference
in effectiveness reflects an actual difference between systems, as opposed to random noise …

Re-using research resources is essential for advancing knowledge and develo**
repeatable, empirically solid experiments in scientific fields, including interactive information …

Tools for automatic subject assignment help deal with scale and sustainability in creating
and enriching metadata, establishing more connections across and between resources and …

In this article, we report on the creation of a publicly available, common evaluation
framework for Violent Scenes Detection (VSD) in Hollywood and YouTube videos. We …

Due to high annotation costs making the best use of existing human-created training data is
an important research direction. We, therefore, carry out a systematic evaluation of …

Abstract The field of Music Information Retrieval has always acknowledged the need for
rigorous scientific evaluations, and several efforts have set out to develop and provide the …

The extraction of pitch information is arguably one of the most important tasks in automatic
music description systems. However, previous research and evaluation datasets dealing …

Traditional pooling-based information retrieval (IR) test collections typically have n= 50 n=
50–100 topics, but it is difficult for an IR researcher to say why the topic set size should really …