Due to the increasing occurrence of very large databases, mining useful information and knowledge from transactions is evolving into an important research area. In the past, many algorithms were proposed for mining association rules, most of which were based on items with binary values. Transactions with quantitative values are, however, commonly seen in real-world applications. In this paper, ...

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...

© 2014. The Authors. Published under Afro Asian Journal of Science and Technology www.aajst.com 26 Amir Ebrahimzadeh Sama technical and vocational training college, Islamic Azad University, Mashhad branch, Mashhad, Iran Abstract due to increasing use of huge databases , mining practical information and useful knowledge from transactions is evolving into an important area. Most data mining metho...

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...

due to the quick growth of the world wide web, retrieval of useful informationfrom the internet for a particular web user or a group of users becomes verydifficult. recommendation systems using web usage mining help providing anadaptive web environment for the web users. this paper presents a novel approachfor page recommendation using fuzzy association rule mining algorithm. thismethod extract...

In order to overcome the difficulty of cognitive and mining for large-scale multi-relationship system, we take the advantages of intelligent computing of FCM (Fuzzy Cognitive Map) and update the traditional FCM to MRFCM (Multi-Relationship based Fuzzy Cognitive Map) for multi-relationship data mining. The state mining of hyper-node and multi-relationship inference of MRFCM are studied and imple...

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...

This paper presents SaM, a split and merge algorithm for frequent item set mining. Its distinguishing qualities are an exceptionally simple algorithm and data structure, which not only render it easy to implement, but also convenient to execute on external storage. Furthermore, it can easily be extended to allow for “fuzzy” frequent item set mining in the sense that missing items can be inserte...