1,721,181 research outputs found
Memory issues in frequent itemset mining
No full textDuring the past decade, many algorithms have been proposed to solve the frequent itemset mining problem, i.e. find all sets of items that frequently occur together in a given database of transactions. Although very efficient techniques have been presented, they still suffer from the same problem. That is, they are all inherently dependent on the amount of main memory available. Moreover, if this amount is not enough, the presented techniques are simply not applicable anymore, or significantly need to pay in performance. In this paper, we give a rigorous comparison between current state of the art techniques and present a new and simple technique, based on sorting the transaction database, resulting in a sometimes more efficient algorithm for frequent itemset mining using less memor
8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004. Proceedings
No full textIn the context of mining frequent itemsets, numerous strategies have been proposed to push several types of constraints within the most well known algorithms. In this paper, we integrate the recently proposed ExAnte data reduction technique within the FP-growth algorithm. Together, they result in a very efficient frequent itemset mining algorithm that effectively exploits monotone constraints
Quick inclusion-exclusion
No full textMany data mining algorithms make use of the well-known Inclusion-Exclusion principle. As a consequence, using this principle efficiently is crucial for the success of all these algorithms. Especially in the context of condensed representations, such as NDI, and in computing interesting measures, a quick inclusion-exclusion algorithm can be crucial for the performance. In this paper, we give an overview of several algorithms that depend on the inclusion-exclusion principle and propose an efficient algorithm to use it and evaluate its complexity. The theoretically obtained results axe supported by experimental evaluation of the quick IE technique in isolation, and of an example application
Knowledge discovery in inductive databases: 3rd International Workshop, KDID 2004, Pisa, Italy, September 20, 2004
No full textProceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations (FIMI'03)
No full textKnowledge discovery in inductive databases: 3rd International Workshop, KDID 2004, Pisa, Italy, September 20, 2004
No full text
Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI 2004)
No full text- …
