Results 101 to 110 of about 45,837 (241)

A partition enhanced mining algorithm for distributed association rule mining systems

Egyptian Informatics Journal, 2015
The extraction of patterns and rules from large distributed databases through existing Distributed Association Rule Mining (DARM) systems is still faced with enormous challenges such as high response times, high communication costs and inability to adapt
A.O. Ogunde, O. Folorunso, A.S. Sodiya
doaj   +1 more source

Mining frequent itemsets a perspective from operations research [PDF]

Many papers on frequent itemsets have been published. Besides somecontests in this field were held. In the majority of the papers the focus ison speed. Ad hoc algorithms and datastructures were introduced.
Kosters, W.A., Pijls, W.H.L.M.
core   +1 more source

Interactive Constrained Association Rule Mining

, 2003
We investigate ways to support interactive mining sessions, in the setting of association rule mining. In such sessions, users specify conditions (queries) on the associations to be generated.
Bussche, Jan Van den, Goethals, Bart
core   +3 more sources

Class Association Rule Pada Metode Associative Classification

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011
Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining.  Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj   +1 more source

Probabilistic Support Prediction: Fast Frequent Itemset Mining in Dense Data

IEEE Access
Frequent itemset mining (FIM) is a highly resource-demanding data-mining task fundamental to numerous data-mining applications. Support calculation is a frequently performed computation-intensive operation of FIM algorithms, whereas storing transactional
Muhammad Sadeequllah, Azhar Rauf, Saif Ur Rehman, Noha Alnazzawi   +3 more
doaj   +1 more source

Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach

Journal of ICT Research and Applications, 2013
Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of
A. V. Senthil Kumar, R. S. D. Wahidabanu
doaj  

WBIN-Tree: A Single Scan Based Complete, Compact and Abstract Tree for Discovering Rare and Frequent Itemset Using Parallel Technique

IEEE Access
Data analytics is an integral part of strategic decision making in various fields but not limited to business, education and healthcare systems. Existing research works focus on the discovery of itemsets with rare antecedents and consequent or frequent ...
Shwetha Rai, Preetham Kumar, K. Nakul Shetty, M. Geetha, B. Giridhar   +4 more
doaj   +1 more source

A Mining-Based Compression Approach for Constraint Satisfaction Problems

, 2013
In this paper, we propose an extension of our Mining for SAT framework to Constraint satisfaction Problem (CSP). We consider n-ary extensional constraints (table constraints). Our approach aims to reduce the size of the CSP by exploiting the structure of
Jabbour, Said, Sais, Lakhdar, Salhi, Yakoub   +2 more
core   +1 more source

Multi-Sorted Inverse Frequent Itemsets Mining

, 2013
14 ...
Sacca', Domenico, Serra, Edoardo, Dicosta, Pietro, Piccolo, Antonio   +3 more
openaire   +2 more sources

Frequent Itemset Mining using QUBO

, 2019
In this paper we propose a R-step approximation to solve frequent itemset mining on quantum hardware like quantum annealing or QAOA. The idea is to search for the set of items where the minimal 2-item frequency is maximal. This can be represented as a maximum clique problem.
openaire   +2 more sources