In this paper we have given a deep insight into the problem of mining approximate top-k patterns from binary matrixes. Our analysis has explored Asso, Hyper+, ...
In this work, we review several greedy state-of-the-art algorithms, namely Asso, Hyper+, and PaNDa+, and propose a methodology to compare the patterns extracted ...
Claudio Lucchese , Salvatore Orlando , Raffaele Perego : Supervised Evaluation of Top-k Itemset Mining Algorithms. DaWaK 2015: 82-94.
In this work, we review several greedy state-of-the-art algorithms, namely Asso, Hyper+, and PaNDa $$^{+}$$ , and propose a methodology to compare the patterns ...
Supervised Evaluation of Top-k Itemset Mining Algorithms. (xsd:string). foaf ... Supervised Evaluation of Top-k Itemset Mining Algorithms. (xsd:string).
This paper formulates the task of targeted mining of the top- high-utility itemsets and proposes an efficient algorithm called TMKU based on the TargetUM ...
Apr 30, 2024 · This paper provides a comprehensive review of the state-of-the-art iHAUIM algorithms, analyzing their unique characteristics and advantages.
Jan 23, 2024 · The Apriori algorithm works by finding relationships among numerous items in a dataset. The method known as association rule mining makes this discovery.
People also ask
How do you evaluate the performance of algorithm in data mining?
What is the primary challenge in the application of the Apriori algorithm for association rule mining in large datasets?
Sep 28, 2023 · The results of experiments on various datasets prove that the FTKHUIM algorithm achieves better results with regard to both the time and search ...
To address this issue, this paper presents a novel algorithm named FTARM (Fast Top-K Association Rule Miner) to efficiently find the set of top-k association ...