Binary image description using frequent itemsets
نویسندگان
چکیده
منابع مشابه
Text clustering using frequent itemsets
Frequent itemset originates from association rule mining. Recently, it has been applied in text mining such as document categorization, clustering, etc. In this paper, we conduct a study on text clustering using frequent itemsets. The main contribution of this paper is three manifolds. First, we present a review on existing methods of document clustering using frequent patterns. Second, a new m...
متن کاملMaximal Frequent Itemsets Mining Using Database Encoding
Frequent itemsets mining is a classic problem in data mining and plays an important role in data mining research for over a decade. However, the mining of the all frequent itemsets will lead to a massive number of itemsets. Fortunately, this problem can be reduced to the mining of maximal frequent itemsets. In this paper, we propose a new method for mining maximal frequent itemsets. Our method ...
متن کاملMining Frequent Itemsets Using Support Constraints
Interesting patterns often occur at varied levels of support. The classic association mining based on a uniform minimum support, such as Apriori, either misses interesting patterns of low support or suuers from the bottleneck of itemset generation. A better solution is to exploit support constraints, which specify what minimum support is required for what itemsets, so that only necessary itemse...
متن کاملMining Frequent Itemsets Using Genetic Algorithm
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm etc., which take too much computer time to compute all the frequent itemsets. By using Genetic Algorithm (GA) we can improve the scenario. The major advantage of using GA in the discovery of frequent itemsets is that...
متن کاملFast mining frequent itemsets using Nodesets
Node-list and N-list, two novel data structure proposed in recent years, have been proven to be very efficient for mining frequent itemsets. The main problem of these structures is that they both need to encode each node of a PPC-tree with pre-order and post-order code. This causes that they are memory consuming and inconvenient to mine frequent itemsets. In this paper, we propose Nodeset, a mo...
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ژورنال
عنوان ژورنال: Journal of Big Data
سال: 2020
ISSN: 2196-1115
DOI: 10.1186/s40537-020-00307-8