Identification of the Patterns Behavior Consumptions by Using Chosen Tools of Data Mining - Association Rules

Abstract

The research and development in sustainable environment, that is a subject of research goal of many various countries and food producers, now, it has a long tradition. The research aim of this paper allows for an identification of the patterns behaviour consumptions by using of association rules, because of knowledge's importance of segmentation differences between consumers and their opinions on current sustainable tendencies.The research area of sustainability will be in Slovakia still discussed, primarily because of impacts and consumer's influencing to product's buying, that are safety to environment and to nature.We emphasize an importance of sustainability in consumer behaviour and we detailed focused on segmentation differences between respondents. We addressed a sample made by 318 respondents. The article aims identifying sustainable consumer behaviour by using chosen data mining tool - association rules.The area of knowledge-based systems is widely overlaps with the techniques in data mining. Mining in the data is in fact devoted to the process of acquiring knowledge from large amounts of data. Its techniques and approaches are useful only when more focused external systems as well as more general systems to work with knowledge. One of the challenges of knowledge-based systems is to derive new knowledge on the basis of known facts and knowledge. This function in a sense meets methods using association rules. Association rules as a technique in data mining is useful in various applications such as analysis of the shopping cart, discovering hidden dependencies entries or recommendation. After an introduction and explanation of the principle of sustainability in consumption, association rules, follows description of the algorithm for obtaining rules from transaction data. Then will present the practical application of the data obtained by questionnaire survey. Calculations are performed in the free data mining software Tanagra.