background: advances in information technology and data collection methods have enabled high-speed collection and storage of huge amounts of data. data mining can be used to derive laws from large data volumes and their characteristics. similarly, fuzzy logic by facilitating the understanding of events is considered a suitable complement to scientific data mining. materials and methods: the pre...

Data mining tools generally deal with highly structured and precise data. However, classical methods fail to handle imprecise or uncertain information. This paper proposes a neuro-fuzzy data mining approach which provides a means to deal with the uncertainty of data. This presents a location-based service collaboration framework and uses the neuro-fuzzy algorithm for data mining. It also introd...

Data mining techniques can be used to discover useful patterns by exploring and analyzing data, so, it is feasible to incorporate data mining techniques into the classification process to discover useful patterns or classification rules from training samples. This paper thus proposes a data mining technique to discover fuzzy classification rules based on the well-known Apriori algorithm. Signif...

This paper is concerned with the data mining application to business process automation. A short tutorial on stages of financial analysis of an enterprise is given. A brief description of data mining components for financial analysis of an enterprise is presented in the paper. The main element of data mining application is fuzzy neural system. The structure of fuzzy neural system includes lingu...

Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions has become an important research area. Most conventional data-mining algorithms identify the relationships among transactions using binary values and find rules at a single concept level. Transactions with quantitative values and items with taxonomic relations...

This paper shows a summarization method. We focus on the construction of fuzzy prototypes by means of typical values. For this purpose, we use a formal framework of measures of comparison of values of attributes of data for the management of fuzzy databases especially for data mining. One of the originalities of this paper lies in the fact that values are fuzzy.

Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of interesting patterns from empirical data. Automated knowledge acquisition of that kind has been an essential aspect of artificial intelligence since a long time and has more recently also attracted considerable attention in the fuzzy sets commu...