Event tracking is the task of discovering temporal patterns of popular events from text streams. Existing approaches for event tracking have two limitations: scalability and inability to rule out non-relevant portions in text streams. In this study, we propose a novel approach to tackle

is that motion-relevant portions of natural gaze behavior can be distinguished from non-relevant. Producing wheelchair movement only from relevant gaze information leads to an increased acceptance of powered wheelchairs in the user group and to improved safety. 1.

Event tracking is the task of discovering temporal patterns of events from text streams. Existing approaches for event tracking have two limitations: scalability and their inability to rule out non-relevant portions within texts in the stream ‘relevant ’ to the event of interest. In this study, we

pre-processing filtration step to e#ectively reduce the search space and the running time of the search operation. Our empirical results on a Prokaryote and a Eukaryote DNA contig dataset, demonstrate e#ective filtration to prune non-relevant portions of the database with up to 2.3timesfaster

the training data set is large. The hyper plane constructed by SVM is dependent on only a portion of the training samples called support vectors that lie close to the decision boundary (hyper plane). Thus, removing any training samples that are not relevant to support vectors might have no effect on building

) dimensionality reduction techniques as a pre-processing filtration step which effectively reduces the search space and running time of the join operation. Our empirical results on a number of Prokaryote and Eukaryote DNA contig datasets demonstrate very efficient filtration to effectively prune non-relevant

of classification applications. Although SVMs have shown potential and promising performance in power disturbances classification, they have been limited by speed particularly when the training data set is large. The hyper plane constructed by SVM is dependent on only a portion of the training samples called

is to select the regions that are closer to the border that separates both target classes: relevant and non-relevant regions. The experimental results showed that the combination of scales produces better results than isolated scales in a relevance feedback process. Furthermore, the interactive method achieved

This volume continues the account of the Aslib-Cranfield project as given in the "Final Report of the First Stage of an Investigation into the Comparative Efficiency of Indexing Systems 11. The major portion of the two years spent on this present stage has been involved with the analysis