With the increment of users and information on the Web, mining processes inspired in the traditional data mining ones have been developed. This new recent area of investigation is called Web Mining. Within this area, we study the analysis of web log files in what is called Web Usage Mining. Different techniques of mining to discover usage patterns from web data can be applied in Web Usage Minin...

Location-aware services using data mining techniques are recent research topics where rules from the data are extracted to provide interesting information. In addition, multi-agent systems are applied in location-based service for autonomous interaction of the system. Different data mining techniques are applied for knowledge discovery from location-based services. However, wireless environment...

A fuzzy logic based expert system has been developed that automatically allocates resources in realtime over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, etc. Potential foes can also be general. The resource manager has been embedded in an electronic game environment. This coevolutionary game fully automates the data mining problem allowing determination of...

Newsday fuzzy systems are applied in many interdisciplinary fields, in which artificial intelligent tools are utilized to analyze different data in the corresponding fields. Under this background, the 2nd International Conference on Fuzzy Systems and Data Mining (FSDM 2016), organized by Macau University of Science and Technology, is scheduled to be held in Macau, December 11–14, 2016. This spe...

Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions is evolving into an important research area. Most conventional data-mining algorithms identify the relationships among transactions using binary values and 7nd rules at a single concept level. Transactions with quantitative values and items with hierarchy rela...

The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many association rules are obtained, the usefulness of them will be reduced. In this paper, we introduce an approach to reduce and summarize the extracted fuzzy association rules after fuzzy data mining. In our approach, in...

Soil Classification deals with the systematic categorization of soils based on distinguished characteristics as well as criteria. We developed Data Mining techniques like: GATree, Fuzzy Classification rules and Fuzzy C Means algorithm for classifying soil texture in agriculture soil data. In this paper, we give a comparative study of developed algorithms. The study is used to compare and analyz...

In this study, we propose the method creating fuzzy control rules based on experiential knowledge. With the advent of data mining techniques, a new way is provided to create fuzzy control rules. With the introduction of incremental data mining techniques, fuzzy control rules can be updated dynamically in time on the condition that massive new data is producing.

. Our simple classification technique on this approach is also able to remove the unwanted data sets that are not useful for making the decision system. We can also combined the fuzzy techniques, TRApriori Algorithm and classification technique to provide the close output. Our classification based fuzzy mining association algorithm can also work on low support values. Due to online notes (Video...

The discretization of values plays a critical role in data mining and knowledge discovery. The representation of information through intervals is more concise and easier to understand at certain levels of knowledge than the representation by mean continuous values. In this paper, we propose a method for discretizing continuous attributes by means of a series of fuzzy sets, which constitutes a f...