Some of the issues in case retrieval and maintenance of case-bases are discussed. Conventionally, nearest neighbor algorithm is applied for retrieval of similar cases. Uniqueness of feature-values is not rewarded in such similarity matching functions. In order to refine the retrieval process, a metric based on successful case usage in the past is incorporated. This metric is shown to be useful ...

In a vector quantisation (VQ) based speaker identification system, a speaker model is created for each speaker from the training speech data by using the k-means clustering algorithm. For an unknown utterance analysed into a sequence of vectors, the nearest prototype classifier is used to identify speaker. To achieve the higher speaker identification accuracy, a fuzzy approach is proposed in th...

We have performed measurements of the magnetic susceptibility of NaV2O5 between 2 and 400 K. The high temperature part is typical of spin 1/2 chains with a nearest–neighbour antiferromagnetic exchange integral of 530 K. We develop a model for the susceptibility of a system with finite chains to account for the low temperature part of the data, which cannot be fitted by a standard Curie-Weiss te...

We have performed measurements of the magnetic susceptibility of NaV2O5 between 2 and 400 K. The high temperature part is typical of spin 1/2 chains with a nearest–neighbour antiferromagnetic exchange integral J of 529 K. We develop a model for the susceptibility of a system with finite chains to account for the low temperature part of the data, which cannot be fitted by a standard Curie-Weiss ...

The nearest neighbour (NN) classifier is often known as a ‘lazy’ approach but it is still widely used particularly in the systems that require pattern matching. Many algorithms have been developed based on NN in an attempt to improve classification accuracy and to reduce the time taken, especially in large data sets. This paper proposes a new classification technique based on kNearest Neighbour...

This research deals with the use of self-organising maps for the classification of text documents. The aim was to classify documents to separate classes according to their topics. We therefore constructed self-organising maps that were effective for this task and tested them with German newspaper documents. We compared the results gained to those of k nearest neighbour searching and k-means clu...

Nearest Neighbour algorithms for pattern recognition have been widely studied. It is now well-established that they offer a quick and reliable method of data classification. In this paper we further develop the basic definition of the standard k-nearest neighbour algorithm to include the ability to resolve conflicts when the highest number of nearest neighbours are found for more than one train...