We have constructed a corpus of news articles in which events are annotated for estimated bounds on their duration. Here we describe a method for measuring inter-annotator agreement for these event duration distributions. We then show that machine learning techniques applied to this data yield coarse-grained event duration information, considerably outperforming a baseline and approaching human...

Twitter is a very popular way for people to share information on a bewildering multitude of topics. Tweets are propagated using a variety of channels: by following users or lists, by searching or by retweeting. Of these vectors, retweeting is arguably the most effective, as it can potentially reach the most people, given its viral nature. A key task is predicting if a tweet will be retweeted, a...

The ability to associate words is an important cognitive skill. In this study we investigate different methods for representing word associations in the brain, using the Remote Associates Test (RAT) as a task. We explore representations derived from free association norms and statistical n-gram data. Although n-gram representations yield better performance on the test, a closer match with the h...

Kinanthropometry is an emerging scientific specialization concerned with the application of measurement to appraise human size, shape, proportion, composition, maturation and gross function. It is the application of anthropometry in sports and Physical Education field to find out performance of human being having the body of different shapes and sizes. At the same time, it is a scientific fact ...

This paper presents an automatic approach to reconstruct human motion using noisy depth data from multiple views. Although multi-view constraints are provided by this setup, it still exhibits great challenges to robustly reconstruct dynamic human performances due to inherent complexity and selfocclusion of human motion. In the insight that the semantics of human motion will supply strong prior ...

The aircraft accident that happened over the last 10 years has been classified into six categories according to their main contributing factors. Those results would have been the same if the figures represented the last 30 years or just the last year. The category is the largest one. It represents 70% of the accident. This figure represents all the accidents where the crew could really have don...

Van Henkle The potential of adaptive networks to learn categorization rules and to model human performance is studied by comparing how natural and artificial systems respond to new inputs, i.e., how they generalize. Like humans, networks can learn a detenninistic categorization task by a variety of alternative individual solutions. An analysis of the constraints imposed by using networks with t...

Computer-based text analysis applications have come a long way since Ellis Page’s Project Essay Grader [1]. Automated assessment applications have achieved better than human reliability and other methods of assisting assessment have opened up additional venues for utilization in the classroom and beyond. However, a lack of understanding of the differences between the different types of applicat...

Human performance, in all its di erent dimensions, is a very complex and interesting topic. In this paper we focus on performance in the workplace which, asides from complex is often controversial. While organizations and generally competitive working conditions push workers into increasing performance demands, this does not necessarily correlates positively to productivity. Moreover, existing ...

Learning categories from examples is a fundamental problem faced by the human cognitive system, and a long-standing topic of investigation in psychology. In this work we focus on the acquisition of natural language categories and examine how the statistics of the linguistic environment influence category formation. We present two incremental models of category acquisition — one probabilistic, o...