An algorithm for fast mining top-rank-k frequent patterns based on Node-list data structure
نویسندگان
چکیده
منابع مشابه
ExMiner: An Efficient Algorithm for Mining Top-K Frequent Patterns
Conventional frequent pattern mining algorithms require users to specify some minimum support threshold. If that specified-value is large, users may lose interesting information. In contrast, a small minimum support threshold results in a huge set of frequent patterns that users may not be able to screen for useful knowledge. To solve this problem and make algorithms more user-friendly, an idea...
متن کاملMining Top-k Approximate Frequent Patterns
Frequent pattern (itemset) mining in transactional databases is one of the most well-studied problems in data mining. One obstacle that limits the practical usage of frequent pattern mining is the extremely large number of patterns generated. Such a large size of the output collection makes it difficult for users to understand and use in practice. Even restricting the output to the border of th...
متن کاملA novel approach for fast mining frequent itemsets use N-list structure based on MapReduce
Frequent Pattern Mining is a one field of the most significant topics in data mining. In recent years, many algorithms have been proposed for mining frequent itemsets. A new algorithm has been presented for mining frequent itemsets based on N-list data structure called Prepost algorithm. The Prepost algorithm is enhanced by implementing compact PPC-tree with the general tree. Prepost algorithm ...
متن کاملMining Frequent Patterns Based on Data Characteristics
Frequent pattern mining is crucial part of association rule mining and other data mining tasks with many practical applications. Current popular algorithms for frequent pattern mining perform differently: some are good for dense databases while the others are ideal for sparse ones. In our previous research, we developed a new frequent pattern mining algorithm named FEM that runs fast on both sp...
متن کاملMining Top-K Frequent Closed Patterns without Minimum Support
In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min `, where k is the desired number of frequent closed patterns to be mined, and min ` is the minimal length of each pattern. An efficient algorithm, called TFP, is developed for mining such patterns without minimum support. Two methods, closed node count and descendant sum are proposed to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2018
ISSN: 1079-8587,2326-005X
DOI: 10.1080/10798587.2017.1340135