Mining Frequent Closed Itemsets with the Frequent Pattern List
نویسندگان
چکیده
The mining of the complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of frequent closed itemsets (FCIs), which results in a much smaller number of itemsets. The approaches to mining frequent closed itemsets can be categorized into two groups: those with candidate generation and those without. In this paper, we propose an approach to mining frequent closed itemsets without candidate generation: with a data structure called the Frequent Pattern List (FPL). We designed the algorithm FPLCI-Mining to mine the frequent closed itemsets (FCIs). Experimental result shows that our method is faster than the previously existing ones.
منابع مشابه
Accelerating Closed Frequent Itemset Mining by Elimination of Null Transactions
The mining of frequent itemsets is often challenged by the length of the patterns mined and also by the number of transactions considered for the mining process. Another acute challenge that concerns the performance of any association rule mining algorithm is the presence of „null‟ transactions. This work proposes a closed frequent itemset mining algorithm viz., Closed Frequent Itemset Mining a...
متن کاملEfficiently Mining Frequent Closed Itemsets by Eliminating Data Redundancies
Recently, data mining has been applied in business information and intelligence systems for discovering interesting patterns and knowledge to support decision making processes. One of the most basic and important tasks of data mining is the mining of frequent itemsets, which are sets of items frequently purchased by customers. Many methods have been proposed for this problem. However, mining th...
متن کاملMining Non- Redundant Frequent Pattern in Taxonomy Datasets using Concept Lattices
In general frequent itemsets are generated from large data sets by applying various association rule mining algorithms, these produce many redundant frequent itemsets. In this paper we proposed a new framework for Non-redundant frequent itemset generation using closed frequent itemsets without lose of information on Taxonomy Datasets using concept lattices. General Terms Frequent Pattern, Assoc...
متن کاملThe Frequent Pattern List: Another Framework for Mining Frequent Patterns
The mining of frequent patterns (or frequent itemsets) plays an essential role in many tasks of data mining. One major methodology for mining frequent patterns is the Apriori-based approach, which is computationally costly because many candidate itemsets have to be generated and verified. More recently, another approach using the Frequent-Pattern Tree (FP-tree) have been suggested to avoid the ...
متن کاملSize of random Galois lattices and number of closed frequent itemsets
Given a sample of binary random vectors with i.i.d. Bernoulli(p) components, that is equal to 1 (resp. 0) with probability p (resp. 1 − p), we first establish a formula for the mean of the size of the random Galois lattice built from this sample, and a more complex one for its variance. Then, noticing that closed α-frequent itemsets are in bijection with closed α-winning coalitions, we establis...
متن کامل