Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a ...

With the explosive growth of data available on the Internet, a recent area of investigation called Web Mining has arise. In this paper, we will study general aspects of this area, principally the process of Web Usage Mining where log files are analyzed. These files register the activity of the user when interact with the Web. In the Web Usage Mining, different techniques of mining to discover u...

The problem of mining association rules in a database are introduced. Most of association rule mining approaches aim to mine association rules considering exact matches between items in transactions. A new algorithm called ―Without expert fuzzy based data mining Based on Fuzzy Similarity to mine new Association Rules ‖ which considers not only exact matches between items, but also the fuzzy sim...

One of the main concerns of an underground coal mining engineer is the safety and stability of the mine. One way that the safety and stability can be ensured is to know and understand the coal mine geology and how it reacts to the mining process. One technique that has shown a lot of success in the coal mining industry for geologic technical evaluation purposes is the coal mine roof rating (CMR...

The discovery of association rule acquire an imperative role in data mining since its inception, which tries to find correlation among the attributes in a database. Classical algorithms/procedures meant for Boolean data and they suffer from sharp boundary problem in handling quantitative data. Thereby fuzzy association rule (i.e., association rule based on fuzzy sets) with fuzzy minimum support...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

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...

Pairs mining targets to mine pairs relationship between entities such as between stocks and markets in financial data mining. It has emerged as a kind of promising data mining applications. Due to practical complexities in the real-world pairs mining such as mining high dimensional data and considering user preference, it is challenging to mine pairs of interest to traders in business situation...

There are various techniques for data mining and data analysis. Data mining is very important in the information retrieval areas especially when the data amounts are very large. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification...

This work examines and proposes a new method for web mining inference based on Fuzzy Cognitive Maps. The web mining inference and knowledge extraction consists of two phases. At the first phase the a priori algorithm is used for web mining and a collection of Association rules is inferred. In the second phase, the set of Association Rules is transformed into a Fuzzy Cognitive Map (FCM). It inve...