This paper describes our work at the sixth NTCIR workshop on the subtask of C-C single language information retrieval. We compared label propagation (LP), K-nearest neighboring (KNN), and relevance feedback (RF) for document re-ranking and found that RF is a more robust technique for performance improvement, while LP and KNN are sensitive to the choice and the number of relevant documents for s...

KNN classification is an improvisational learning mode, in which they are carried out only when a test data predicted that set suitable K value and search the nearest neighbors from whole training sample space, referred them to lazy part of classification. This has been bottleneck problem applying due complete neighbors. In this paper, one-step computation proposed replace The actually transfor...

Zusammenfassung. Eine wichtige Frage in der mobilen Robotik ist die sichere Navigation in unbekannten Umgebungen unter der Anwendung preiswerter Sensorik. Solch eine Navigation kann ein künstliches Neuronales Netz (kNN) übernehmen, welches die Kopplung der Sensoren des Roboters mit dessen Antriebssystem herstellt. ” Neuro Evolution of Augmenting Topologies“ (NEAT) von Stanley und Miikkulainen [...

In this paper, we investigate the effectiveness of Citation K-Nearest Neighbors (KNN) learning with noisy training datasets. We devise an authority measure associated with each training instance that changes based on the outcome of Citation KNN classification. The authority is increased when a citer’s classification had been right; and vice versa. We show that by modifying only these authority ...

Heterogeneous features of thyroid nodules in ultrasound images is very difficult task when radiologists and physicians manually draw a complete shape of nodule, size and shape, image or distinguish what type of nodule is exist. Segmentation and classification is important methods for medical image processing. Ultrasound imaging is the best way to prediction of which type of thyroid is there. In...

The World Health Organization (WHO) and drug regulators in many countries maintain databases for adverse drug reaction reports. Data duplication is a significant problem in such databases as reports often come from a variety of sources. Most duplicate detection techniques either have limitations on handling large amount of data or lack effective means to deal with data with imbalanced label dis...