The challenges of the standard clustering methods and the weaknesses of Apriori algorithm in frequent termset clustering formulate the goal of our research. Based on Association Rules mining, an efficient approach for Web Document Clustering (ARWDC) has been devised. An efficient Multi-Tire Hashing Frequent Termsets algorithm (MTHFT) has been used to improve the efficiency of mining association...

This paper shows a new method based on association rule mining and ontology for the classification of web pages. This work is pruning of association rules, generated by mining process. The main complexity arises due to the fact that there are various number of text documents that are considered for generating the association rules using the A-priori algorithm. But these rules that were generate...

Data mining, also known as knowledge discovery in databases, is the process of discovery potentially useful, hidden knowledge or relations among data from large databases. An important topic in data mining research is concerned with the discovery of association rules. The majority of databases are distributed nowadays. In this paper is presented an algorithm for mining fuzzy association rules f...

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...

Association rule mining is the most important technique in the field of data mining. The main task of association rule mining is to mine association rules by using minimum support thresholds decided by the user, to find the frequent patterns. Above all, most important is research on increment association rules mining. The Apriori algorithm is a classical algorithm in mining association rules. T...

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions with quantitative values are however commonly seen in real-world applications. The fuzzy concepts are used to represent item importance, item qu...

In this paper, we examine the issue of mining association rules among items in a large database of sales transactions. Mining association rules means that given a database of sales transactions, to discover all associations among items such that the presence of some items in a transaction will imply the presence of other items in the same transaction. The mining of association rules can be mapp...

Many algorithms to mine the association rules are divided into two stages, the first is to find the frequent set; the second is use the frequent set to generate association rules. This proposal discuss the respective characteristics and .shortcoming of the current algorithms to mine association rules and propose another method to mine faster; unlike the other algorithms, this algorithm emphasis...

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...