Wireless Sensor Networks (WSN) generates a huge amount of data for efficient application of discovering essential knowledge from it is important. Usually, WSN data is generated in streams and forwarded to a sink. Raw data leads to higher communication overhead adversely affecting WSN performance. Association mining processes data to locate frequent patterns. Thus, when association mining is app...

This article provides a survey of the available literature on fuzzy Web mining. The di-erent aspects of Web mining, like clustering, association rule mining, navigation, personalization, Semantic Web, information retrieval, text and image mining are considered under the existing taxonomy. The role of fuzzy sets in handling the di-erent types of uncertainties/impreciseness is highlighted. A hybr...

© 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...

This article proposes an algorithm for data mining that presents a new measure for assistance in the extraction of knowledge. The algorithm uses association rules to extract rules from the databases and fuzzy logic for the classification and comparison of the collected rules. Key-words: data mining, association rules, fuzzy logic, similarity and algorithm of the inverse confidence.

A Fuzzy Mining Algorithm for Association-Rule Knowledge Discovery" (2005). ABSTRACT ABSTRASCT Due to increasing use of very large database and data warehouses, discovering useful knowledge from transactions is becoming an important research area. On the other hand, using fuzzy classification in data mining has been developed in recent years. Hong and Lee proposed a general learning method that ...

In this paper, Fuzzy concept hierarchies are used for multi-level association rule mining from large datasets via Attribute-Oriented Induction approach [1]. In this the process of fuzzy hierarchical induction approach is used and extends it with two new characteristics which improve applicability of the original approach in data mining. The proposed drilling-down approach of fuzzy induction mod...

the concept of intelligently controlling the search process of gravitational search algorithm (gsa) is introduced to develop a novel data mining technique. the proposed method is called fuzzy gsa miner (fgsa-miner). at first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major ro...

A number of techniques have been developed to turn data into useful knowledge. Most of the algorithms in data mining find association rules among transactions using binary values and at single concept level. However it will be more exciting to discover hierarchical association rules for decision makers. In this work we have integrated association rule mining with fuzzy set theory and hierarchy....

In today’s life Intrusion Detection System gain the attention, because of ability to detect the intrusion access efficiently and effectively as security is the major issue in networks. This system identifies attacks and reacts by generating alerts or blocking the unwanted data/traffic. Intrusion Detection System mainly classified as Anomaly based intrusion detection systems that have benefit of...

We have been using fuzzy data mining techniques to extract patterns that represent normal behavior for intrusion detection. In this paper we describe a variety of modifications that we have made to the data mining algorithms in order to improve accuracy and efficiency. We use sets of fuzzy association rules that are mined from network audit data as models of " normal behavior. " To detect anoma...