This chapter describes realization of distributed approach to continuous queries with kNN join processing in the spatial telemetric data warehouse. Due to dispersion of the developed system, new structural members were distinguished: the mobile object simulator, the kNN join processing service, and the query manager. Distributed tasks communicate using JAVA RMI methods. The kNN queries (k Neare...

This article reports on a modification of the user-kNN algorithm that measures the similarity between users based on the similarity of text reviews, instead of ratings. We investigate the performance of text semantic similarity measures and we evaluate our text-based user-kNN approach by comparing it to a range of ratings-based approaches in a ratings prediction task. We do so by using datasets...

In this study, we develop a two-class classification system based on a committee of k-Nearest Neighbour (kNN) classifiers. The system includes a sequence of simple data preprocessing steps. Each committee consists of 5 kNN classifiers of different architectures. Each classifier on the committee takes in a different set of features. The classification system is then applied to a set of microarra...

The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed ke...

Currently, in the Republic of Korea, despite the very-low-birth rate, the birth rate and number of preterm infants are markedly increasing. Neonatal deaths and major complications mostly occur in premature infants, especially very-low-birth-weight infants (VLBWIs). VLBWIs weigh less than 1,500 g at birth and require intensive treatment in a neonatal intensive care unit (NICU). The operation of ...

Content based image retrieval (CBIR) from large resources has become a dominant research field and found wide interest nowadays in many applications. In this thesis work, we design and implement a content based image retrieval system that uses color and texture as visual features to describe the content of an image region. We use k-nearest neighbor (knn) and HSV color model to extract feature o...

Neighborhood Components Analysis (NCA) is a popular method for learning a distance metric to be used within a k-nearest neighbors (kNN) classifier. A key assumption built into the model is that each point stochastically selects a single neighbor, which makes the model well-justified only for kNN with k = 1. However, kNN classifiers with k > 1 are more robust and usually preferred in practice. H...

An intrusion detection system (IDS) detects unauthorized manipulations of computer systems. Operation as feature reduction (including feature extraction and feature selection) plays an important role in the sense of improving classification performance and reducing the computational complexity of intrusion detection system. Feature reduction is even more important at online detection when less ...