Banking product extension is a source of widespread information and advertisement, especially fluently supported by Internet media. Case-Based Reasoning (CBR) is an Artificial Intelligence method being used as extension tool, with e-commerce as fast growing application field. Article presents the methodology of applying similarity measures of CBR method to extract bank account products most similar to presented customer preferences. Local similarity measures as well as global similarity measure are described for each account attribute. Computer application based on this method was created within project and applied to search banking products. Real world data of 142 Polish banks’ accounts were used in computations. Examples of search for an account are presented to show searching results and different case adaptation techniques.
The aim of this study was to examine the possibility of using characteristic features (physical and behavioral) of selected animals in the process of creating neural classification models. A set of specific properties constitutes the basis for the use of a classifier in the form of an artificial neural network. Its construction is based on the need to obtain information encoded in the form of an analyzed image. In this study, examples of potential applications of image neural analysis were presented and possibilities of using this technique in the field of veterinary medicine were proposed. Examples of potential applications were listed. The method of identification and description of characteristic areas visible in the ultrasound image of a cow’s uterus were characterized. The need for the skillful gathering of empirical graphic data was considered as vital in order to conduct the extraction of features and the creation of a self-learning representative set.