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Divider-based algorithms for hierarchical tree partitioning

Irene Finocchi, Rossella Petreschi
2004 Discrete Applied Mathematics  
We present algorithms for computing hierarchical decompositions of trees satisfying di erent optimization criteria, including balanced cluster size, bounded number of clusters, and logarithmic depth of  ...  The use of t-dividers, combined with a reduction to a classical scheduling problem, yields an algorithm that, given a n-vertex tree T , builds in O(n log n) worst-case time a hierarchical decomposition  ...  Acknowledgements The authors wish to thank three anonymous referees for their careful review of the paper and for their constructive comments.  ... 
doi:10.1016/s0166-218x(03)00443-8 fatcat:nyxggxstjjft7ldp4qqcgo5idy

An Analytical Assessment on Document Clustering

Pushplata, Ram Chatterjee
2012 International Journal of Computer Network and Information Security  
Clustering is related to data mining for information retrieval. Relevant information is retrieved quickly while doing the clustering of documents.  ...  Hierarchical Clustering Algorithm [10, 11] 1. Partitioned Clustering Algorithm [3, 20] In partitioned clustering data is divided into partitions.  ...  For example there is a base cluster graph for the above three documents define in the suffix tree: Base clusters are clustering by using single linkage clustering algorithm.  ... 
doi:10.5815/ijcnis.2012.05.08 fatcat:4nt2ryrsbjetzfpbzccloqwnmq

Implementation of Clustering Algorithms for Real Time Large Datasets

The various approaches for clustering grid clustering, density based clustering, hierarchical methods, partitioning approaches.  ...  In this survey paper we focused on all these algorithms for large datasets like big data and make a report on comparison among them. The main metric is time complexity to differentiate all algorithms.  ...  Different methods for clustering includes hierarchical methods [1] , partitional approaches, density based approaches [5] , grid based approaches [7] [8] and model based techniques.  ... 
doi:10.35940/ijitee.c2570.0981119 fatcat:46k3kpwmmjemdivj2wafgivoae

Subject Review: Text Clustering Algorithms

Zuhair Hussein Ali, Amal Abbas Kadhim, Azal Minshed Abid
2020 International Journal of Engineering Research and Advanced Technology  
These algorithms include hierarchal algorithms, partitioning algorithms, density based algorithms and grid based algorithm.  ...  STING Clustering Algorithm STING stands for STatistical Information Grid. The main idea of STING algorithm based on dividing the dataset into a hierarchy structure.  ...  Figure 1 presents the main algorithms for big data clustering, that consists of hierarchical algorithms, partition based algorithms, density based algorithms and grid based algorithms.  ... 
doi:10.31695/ijerat.2020.3646 fatcat:t2fs2gfarbedvig6ityvdwihqe

An Efficient Way for Clustering Using Alternative Decision Tree

2012 American Journal of Applied Sciences  
Compared to existing clustering algorithms either partition or hierarchical, our new method is more robust and easy to reach the solution of real world complex business problem.  ...  Approach: Our proposed method combines tree projection and condition for clustering formation and also is capable to produce a customizable cluster for varying kind of data along with varying number of  ...  The most commonly used clustering algorithms can be typically classified into four types: Hierarchical Method (BIRCH, CURE), Partitional Clustering (Kmeans, K-prototypes, K-mode), Density-based Clustering  ... 
doi:10.3844/ajassp.2012.531.534 fatcat:xrwpt4nc6zgdfaodzto2uvkloe

Comparative Analysis on Medical Images using SPIHT, STW and EZW

Jayant Kumar Rai, Chandrashekhar Kamargaonkar
2016 International Journal of Engineering Research and  
In this paper we compared the wavelet based algorithms such are Embedded Zero tree Wavelet (EZW), Set partitioning in Hierarchical Trees (SPIHT) and spatial orientation tree Wavelet (STW).  ...  STW is the best algorithms as compared to others image compression method. It gives high CR and PSNR with better image quality.  ...  Fig. 1 SPIHT 1 Set partitioning in Hierarchical Trees (SPIHT) is the most important algorithms based on wavelet coefficient.  ... 
doi:10.17577/ijertv5is020531 fatcat:covc3a7vc5bdddbe66xjsqq4la

Binary Classication Tree for Multiclass Classication with Observation-based Clustering

Maythapolnun Athimethphat, Boontarika Lerteerawong
1970 ECTI Transactions on Computer and Information Technology  
Unlike a traditional class-clustering approach, this observation-based algorithm allows one class to appear in two meta-classes so it can be examined in both sub-trees.  ...  The experiment shows how our proposed algorithm (BCTOB) performed on different data sets, compared with other binary classification tree algorithms.  ...  Unsupervised techniques like hierarchical clustering and k-means are used in finding the best partition for splitting (e.g., [2 -4 ] , [6] , [13] ).  ... 
doi:10.37936/ecti-cit.201262.54335 fatcat:33z5hgz25zhj3mfi22ikzvx3le

Review of Clustering Techniques for Finding the Similarity in Articles

Usha Rani, Shashank Sahu
2016 International Journal of Computer Applications  
This paper reviews various techniques of clustering which can be divided mainly into two groups that are hierarchical and partitional clustering.  ...  Keywords Clustering, Hierarchical clustering, Partitional clustering.  A graph partitioning algorithm is used to partition the large cluster into smaller sub clusters.  Repeatedly merging of sub clusters  ...  It is based on two phases: PARTITIONAL CLUSTERING In partitional clustering the objects are divided into k partition, where each partition represents a cluster.  ... 
doi:10.5120/ijca2016912329 fatcat:a46ihrcu6zaizoy5zydxbaashy

An Analytic Survey On Current Clustering Technique of data Categorizing and Retrieving

Snehlata Bhadoria, U. Datta
2016 International Journal Of Engineering And Computer Science  
It tries to divide data into partition based on some evolutionary criteria.  ...  The Partitioned technique, Hierarchical technique, Density-Based technique, Grid-Based technique and Model-Based technique are widely implemented for clustering.  ... 
doi:10.18535/ijecs/v5i5.28 fatcat:xvkbvfwnq5dunozo5oerk7bhhu

Review of Clustering Techniques in Control System

Saumya Singh, Smriti Srivastava
2020 Procedia Computer Science  
This paper majorly emphasises on critical review of clustering algorithms used in control systems, but a brief overview is also given about all major algorithms.  ...  This paper majorly emphasises on critical review of clustering algorithms used in control systems, but a brief overview is also given about all major algorithms.  ...  A hierarchical clustering is based on dendogram like structure, which divides or merge data like branches of tree in contrast with this partitional clustering bifurcate data set into subsets, based on  ... 
doi:10.1016/j.procs.2020.06.032 fatcat:z4smiadd35artavs3lvxztn4dq

Parallel clustering algorithms

Xiaobo Li, Zhixi Fang
1989 Parallel Computing  
Although the parallel clustering algorithms have been used for many applications, the clustering tasks are applied as preprocessing steps for parallelization of other algorithms too.  ...  Based on the purposed  ...  [7] divided the whole clustering algorithms into 6 categories: Partitioning, Hierarchical, grid-based, density-based, model-based and graph-based clustering algorithms.  ... 
doi:10.1016/0167-8191(89)90036-7 fatcat:uly53om5cjgzvcfdft5mkikafe

A Performance Evaluation of SMCA Using Similarity Association & Proximity Coefficient Relation For Hierarchical Clustering

Mayank Gupta, Ritesh Jain
2014 International Journal of Engineering Trends and Technoloy  
But problem are always arises for finding a new algorithm and process for extracting knowledge for improving accuracy and efficiency.  ...  This type of dilemma motivated us to develop new algorithm and process for clustering problems.  ...  Farley and Raftery suggest dividing the clustering methods into two main groups: hierarchical and partitioning methods.  ... 

Hierarchical Clustering- An Efficient Technique of Data mining for Handling Voluminous Data

Shuhie Aggarwal, Parul Phoghat, Seema Maitrey
2015 International Journal of Computer Applications  
Clustering can be done by different number of methods such as-partitioning based methods, methods based on hierarchy, density based ,grid based ,model based methods and constraint based clustering.  ...  In this survey paper review of clustering and its different techniques is done with special focus on Hierarchical clustering.  ...  COMPARING PERFORMANCE OF ALGORITHMS The hierarchical clustering algorithm BIRCH clusters the data objects by building CF trees for the data sets.  ... 
doi:10.5120/ijca2015907081 fatcat:7vhp7axkovewzfvzfhidgylt6q

Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering

Rodrigo Aldecoa, Ignacio Marín, Carl Kingsford
2010 PLoS ONE  
Finally, Jerarca provides optimal partitions of the trees using statistical criteria based on the distribution of intra- and intercluster connections.  ...  clustering; 3) Automatic evaluation of the hierarchical trees to obtain optimal partitions; and, 4) Outputs compatible with popular software such as MEGA and Cytoscape.  ...  Acknowledgments The authors would like to thank Vicente Arnau for his contributions in the development of the original UVCluster program, and Antonio Marco for his suggestions about how to implement the  ... 
doi:10.1371/journal.pone.0011585 pmid:20644733 pmcid:PMC2904377 fatcat:inavjyuiincjlkbu6l723fzmmi

A Survey Of Hierarchical Clustering Algorithms

Marjan Kuchaki Rafsanjani, Zahra Asghari Varzaneh, Nasibeh Emami Chukanlo
2012 Journal of Mathematics and Computer Science  
They can be divided into categories: Sequential algorithms, Hierarchical clustering algorithms, Clustering algorithms based on cost function optimization and others.  ...  In this paper, we discuss some hierarchical clustering algorithms and their attributes, and then compare them with each other.  ...  The authors would like to express their thanks to referees for their comments and suggestions which improved the paper.  ... 
doi:10.22436/jmcs.05.03.11 fatcat:7u77etp4svgt3osb2ab2ofqv34
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