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Distributed Sequential Pattern Mining: A Survey and Future Scope
2014
International Journal of Computer Applications
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A large research has been done on sequential pattern mining on various distributed environments like Grid, Hadoop, Cluster, Cloud, etc. ...
Distributed sequential pattern mining is the data mining method to discover sequential patterns from large sequential database on distributed environment. ...
This paper [34] proposed Distributed Mar-Miner (DMM) algorithm for mining of maximal frequent itemsets from databases. A frequent itemset is maximal if none its supersets is frequent. ...
doi:10.5120/16461-6187
fatcat:7ggeuyoqwnfzhnhwjixufttpua
A Comparative Study of Association Rule Mining Algorithms on Grid and Cloud Platform
[article]
2017
arXiv
pre-print
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Grid and cloud are the emerging platform for distributed data processing and various association rule mining algorithms have been proposed on such platforms. ...
This survey article integrates the brief architectural aspect of distributed system, various recent approaches of grid based and cloud based association rule mining algorithms with comparative perception ...
[29] that mines the maximal frequent itemsets on a Data Grid System which is based on Globus Toolkit. Database is evenely distributed across nodes of Data Grid. ...
arXiv:1709.07594v1
fatcat:6jneovykqvfq5ja6vmds3akziy
Performance study of distributed Apriori-like frequent itemsets mining
2009
Knowledge and Information Systems
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2019 pre-print arXiv:1903.03008v1 fatcat:oo7zvbxkj5fd7kdbzqizijyaw4
In this article, we focus on distributed Apriori-based frequent itemsets mining. We present a new distributed approach which takes into account inherent characteristics of this algorithm. ...
Our performance evaluation is done on a large cluster of workstations using the Condor system and its workflow manager DAGMan. ...
Some research works in maximal frequent itemsets mining are reported in [16] and [17] . However, there are only few algorithms adapted to nowadays distributed systems such as the grid. ...
doi:10.1007/s10115-009-0205-3
fatcat:ttqlqd6fafej7pzznfxcjlsiyi
Executing association rule mining algorithms under a Grid computing environment
2011
Proceedings of the Workshop on Parallel and Distributed Systems Testing, Analysis, and Debugging - PADTAD '11
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A Grid infrastructure distributed in nine sites around France, for research in large-scale parallel and distributed systems. ...
This load imbalance is due to the dynamic nature of data mining algorithms (i.e. we cannot predict the load before execution) and the heterogeneity of Grid computing systems. ...
Data mining is one of these applications. ...
doi:10.1145/2002962.2002973
dblp:conf/issta/TliliS11
fatcat:igb2rbh2yjgizhsaigjhms2hqu
Mining Association Rules on Grid Platforms
[chapter]
2012
Lecture Notes in Computer Science
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In this paper we propose a dynamic load balancing strategy to enhance the performance of parallel association rule mining algorithms in the context of a Grid computing environment. ...
This strategy is built upon a distributed model which necessitates small overheads in the communication costs for load updates and for both data and work transfers. ...
Proposed a heuristic data distribution scheme for data mining applications on grid environments [16] . ...
doi:10.1007/978-3-642-29737-3_23
fatcat:m5sbvwpr6zcnxaq47hi5emjjje
Knowledge Discovery on the Grid
[chapter]
2009
Data Mining and Knowledge Discovery in Real Life Applications
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Grid-based frequent itemsets mining The frequent itemsets mining task is at the core of various data mining applications. ...
The focus then is on mining frequent itemsets on distributed datasets over the Grid. ...
Data Mining and Knowledge Discovery in Real Life Applications This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like ...
doi:10.5772/6439
fatcat:g2uyj2fbm5h2dlf5ftl5jknvi4
Flexible Approach for Data Mining using Grid based Computing Concepts
2017
International Journal Of Engineering And Computer Science
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This paper discusses how distributed and Grid computing can be used to support distributed data mining. In particular, a distinction is made between distributed and Grid-based data mining methods. ...
Here we present the state of the art about the major data mining techniques, systems and approaches. ...
databases on a data Grid system. ...
doi:10.18535/ijecs/v6i6.26
fatcat:2t3fpjm3kfabtk6famh2i57bjm
Review of Apriori Based Algorithms on MapReduce Framework
[article]
2017
arXiv
pre-print
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The Apriori algorithm that mines frequent itemsets is one of the most popular and widely used data mining algorithms. ...
MapReduce is an efficient, scalable and simplified programming model for large scale distributed data processing on a large cluster of commodity computers and also used in cloud computing. ...
Hadoop Distributed File System Hadoop Distributed File System (HDFS) is distributed file system that holds a large volume of data in terabytes or petabytes scale and provides fast and scalable access to ...
arXiv:1702.06284v1
fatcat:khpoq35xcfhzfc4v7mm362bbyq
Grid-based Approaches for Distributed Data Mining Applications
[article]
2017
arXiv
pre-print
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We propose a new distributed clustering approach and a distributed frequent itemsets generation well-adapted for grid environments. ...
In this paper, we present grid-based approaches for two basic data mining applications, and a performance evaluation on an experimental grid environment that provides interesting monitoring capabilities ...
Distributed frequent itemsets mining Discovering frequent itemsets is a crucial task in data mining. ...
arXiv:1703.09807v1
fatcat:qb3todc5mzf65d64ougsnorytm
Formal Concept Analysis for Digital Ecosystem
2006
2006 5th International Conference on Machine Learning and Applications (ICMLA'06)
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This paper offers a brief overview of FCA and proposes to apply FCA as a tool for analysis and visualization of data in Digital ecosystem, and also discusses the applications of data mining for Digital ...
Many research works of various areas show that concept lattices structures is an effective platform for data mining, machine learning, information retrieval, software engineer, etc. ...
Acknowledgements This work is supported by the project of EU IST Network of Excellence "OPAALS". ...
doi:10.1109/icmla.2006.24
dblp:conf/icmla/Fu06
fatcat:nq45j5m7ffeflcgmjxpnr52gyi
Mining@Home:Public resource Computing For Distributed Data Mining
[chapter]
2008
From Grids to Service and Pervasive Computing
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In this paper, we focus on one of the main data mining problem: the extraction of closed frequent itemsets from transactional databases. ...
Finally, we evaluate the execution of our data mining job on such network. ...
In those systems, a set of data mining tasks can be distributed across several machines in an ad-hoc environment. ...
doi:10.1007/978-0-387-09455-7_16
fatcat:mkdevmdzsfgnpl243gmw6jpfz4
Survey on Distributed Data Mining in P2P Networks
[article]
2012
arXiv
pre-print
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Careful attention in the usage of distributed resources of data, computing, communication, and human factors in a near optimal fashion are paid by distributed data mining. ...
To solve these problems, Distributed Data Mining (DDM) has emerged as a hot research area. ...
on the set of frequent k-itemsets obtained. ...
arXiv:1205.3231v1
fatcat:5tajkiqlg5hufjrhiy3xzz4d4m
Privacy-Preserving Data Mining on Moving Object Trajectories
2007
2007 International Conference on Mobile Data Management
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a particular purpose. ...
Runes have angular shapes and lack horizontal lines because the primary storage medium was wood, although they may also be found on jewelry, tools, and weapons. ...
An itemset Y is a maximal probabilistically frequent itemset if there does not exists a probabilistically frequent itemset X such that Y ⊂ X. ...
doi:10.1109/mdm.2007.18
dblp:conf/mdm/GidofalviHP07
fatcat:lcpik3nzongpbfj3n2jnr3sjgm
Fast Mining of Finding Frequent Patterns in Transactional Database using Incremental Approach
2015
International Journal of Applied Information Systems
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Also, it shortens the response time to a query for the set of frequent items. ...
This paper presents a structure for simply, easily and competently parallelizing data mining algorithms for those huge datasets together with the incremental mining. ...
Parallelization in Data Mining Zhang et. al. proposed parallel FP-growth algorithm [6] on distributed machines. ...
doi:10.5120/ijais15-451369
fatcat:r4zg4zt7s5er3it7drvz5lap3m
Parallel and distributed association mining: a survey
1999
IEEE Concurrency
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Data Mining S ince its inception, association rule mining has become one of the core data-mining tasks and has attracted tremendous interest among researchers and practitioners. 1 ARM is undirected or ...
The author surveys the state of the art in parallel and distributed association-rule-mining algorithms and uncovers the field's challenges and open research problems. ...
A frequent itemset is maximal if it is not a subset of any other frequent itemset. An association rule is an expression A ⇒ B, where A and B are itemsets. ...
doi:10.1109/4434.806975
fatcat:v2icq37pfrfivjs5wfrdklyrqm
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