The ability to perform tasks similarly to how a specific human would perform them is valuable in future automation efforts across several areas. This paper presents a k-nearest neighbor trajectory generation methodology that creates trajectories similar to those of a given user in the Space Navigator environment using cluster-based player modeling. This method improves on past efforts by genera...

In this paper we compare several popular rank aggregation methods by accuracy of finding the true (correct) ranked list. Our research reveals that under most common circumstances simple methods such as the average or majority actually tend to outperform computationally-intensive distance-based methods. We then conduct a study to compare how actual people aggregate ranks in a group setting. Our ...

We study the problem of predicting student performance in an online course. Our specific goal is to identify at an early stage of the course those students who have a high risk of failing. We employ the k-nearest neighbour method (KNN) and its many variants on this problem. We present extensive experimental results from a 12-lesson course on touch-typing, with a database of close to 15000 stude...

The edited technique is of great importance in pattern recognition. The classical edited fuzzy technique use fuzzy k nearest neighbors(FKNN) to take out some useless samples which was classified erroneously in the editing process. In this paper, a proposed edited fuzzy k nearest neighbors based on threshold is developed, which not only consider the maximum membership value but also consider tha...

The goal of traditional multi-instance learning (MIL) is to predict the labels of the bags, whereas in many real applications, it is desirable to get the instance labels, especially the labels of key instances that trigger the bag labels, in addition to getting bag labels. Such a problem has been largely unexplored before. In this paper, we formulate the Key Instance Detection (KID) problem, an...

In this paper we address two issues concerning real-world time-continuous emotion detection from videos of users’ faces: (i) the impact of weak ground truth on the emotion detection accuracy and (ii) the impact of the users’ facial expressiveness on the emotion detection accuracy. We implemented an appearance-based emotion detection algorithm that uses Gabor features and a k nearest neighbors c...

We compared the quality of prediction of word variables based on a Dutch word association and text corpus. We derived estimates for: valence, arousal, dominance, concreteness and age of acquisition (AoA) for 2831 words. Based on the similarity between words we: (1) used projections on a dimension identified as the variable in question in a multidimensional representation, (2) used the k-nearest...

Abstract: This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted with visual stimulation, leading to biological brain responses known as Visual Evoked Potentials. We evaluated a novel method, using only 8 occipital electrodes and the energy of differential E...

This paper describes our English patent mining system for NTCIR-7 patent mining task which maps a research paper abstract into IPC taxonomy. Our system is basically under the k-Nearest Neighboring framework, in which various similarity calculation and ranking methods are used. We employ two re-ranking techniques to improve the performance by the use of richer features. Our systems performed wel...