Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Frequent itemset minning with trie data structure and parallel execution with PVM
Date
2007-10-03
Author
Guner, Levent
Karagöz, Pınar
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
150
views
0
downloads
Cite This
Apriori algorithm is one of the basic algorithms introduced to solve the problem of frequent itemset mining (FIM). Since there is a new generation of affordable computers with parallel processing capability and it is easier to set up computer clusters, we can develop more efficient parallel FIM algorithms for these new systems. This paper investigates the use of trie data structure in parallel execution of Apriori algorithm, the potential problems during implementation, performance comparison of several parallel implementations and in order to increase the efficiency, proposes a new way of message passing for parallel Apriori on a computer cluster with PVM.
Subject Keywords
Message passing
,
Trie
,
Parallel execution
,
PVM
,
Apriori
URI
https://hdl.handle.net/11511/62444
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Hierarchical Parallelization of the Multilevel Fast Multipole Algorithm (MLFMA)
Gurel, Levent; Ergül, Özgür Salih (2013-02-01)
Due to its O(NlogN) complexity, the multilevel fast multipole algorithm (MLFMA) is one of the most prized algorithms of computational electromagnetics and certain other disciplines. Various implementations of this algorithm have been used for rigorous solutions of large-scale scattering, radiation, and miscellaneous other electromagnetics problems involving 3-D objects with arbitrary geometries. Parallelization of MLFMA is crucial for solving real-life problems discretized with hundreds of millions of unkno...
MODELLING OF KERNEL MACHINES BY INFINITE AND SEMI-INFINITE PROGRAMMING
Ozogur-Akyuz, S.; Weber, Gerhard Wilhelm (2009-06-03)
In Machine Learning (ML) algorithms, one of the crucial issues is the representation of the data. As the data become heterogeneous and large-scale, single kernel methods become insufficient to classify nonlinear data. The finite combinations of kernels are limited up to a finite choice. In order to overcome this discrepancy, we propose a novel method of "infinite" kernel combinations for learning problems with the help of infinite and semi-infinite programming regarding all elements in kernel space. Looking...
Asymptotically optimal importance sampling for Jackson networks with a tree topology
Sezer, Ali Devin (2010-02-01)
This note describes an importance sampling (IS) algorithm to estimate buffer overflows of stable Jackson networks with a tree topology. Three new measures of service capacity and traffic in Jackson networks are introduced and the algorithm is defined in their terms. These measures are effective service rate, effective utilization and effective service-to-arrival ratio of a node. They depend on the nonempty/empty states of the queues of the network. For a node with a nonempty queue, the effective service rat...
Benchmark Solutions of Large Problems for Evaluating Accuracy and Efficiency of Electromagnetics Solvers
Gurel, Levent; Ergül, Özgür Salih (2011-07-08)
We present a set of benchmark problems involving conducting spheres and their solutions using a parallel implementation of the multilevel fast multipole algorithm (MLFMA). Accuracy of the implementation is tested by comparing the computational results with analytical Mie-series solutions. Reference solutions are made available on an interactive website to evaluate and compare the accuracy and efficiency of fast solvers. We also demonstrate the capabilities of our solver on real-life problems involving compl...
Efficient parallelization of multilevel fast multipole algorithm
Ergül, Özgür Salih (null; 2006-11-10)
We report our efforts for the solution of large electromagnetics problems accurately and efficiently with the parallel multilevel fast multipole algorithm. We carefully investigate different stages of the parallelization and identify the bottlenecks to develop new strategies. The required modifications are implemented in order to increase the efficiency of the solutions of scattering problems involving various geometries.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
L. Guner and P. Karagöz, “Frequent itemset minning with trie data structure and parallel execution with PVM,” 2007, vol. 4757, p. 289, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62444.