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FastIsomapVis: A Novel Approach for Nonlinear Manifold Learning

Mahwish Yousaf, Tanzeel U. Rehman, Dong Liang Liao, Naji Alhusaini, Li Jing
2020 IEEE Access  
The FastIsomapVis uses hierarchal divide, conquer, and combine approach through two algorithms, which are randomized division tree (KD-tree) and Dijkstra Buckets Double (DKD).  ...  In this paper, we propose a novel technique called the FastIsomapVis for the above problems of the classical Isomap.  ...  In Section 3, we propose the FastIsomapVis method for large-scale and highdimensional datasets with divide, conquer, and combined approach.  ... 
doi:10.1109/access.2020.3017954 fatcat:6xqsi7n5srdtnoylxbjigq33wy

An Efficient Divide-and-Conquer Algorithm for Morphological Filters

Shan Lou, Xiangqian Jiang, Paul J. Scott
2013 Procedia CIRP  
However the Delaunay triangulation on which the alpha shape method depends is costly for large areal data.  ...  This paper proposes a divide-and-conquer method as an optimization to the alpha shape method aiming to speed up its performance.  ...  The performance evaluation reveals that the divide-and-conquer algorithm achieves superior performance over the original alpha shape method.  ... 
doi:10.1016/j.procir.2013.08.024 fatcat:5uxt473panefxpbffbhyqobwh4

Divide-and-Conquer Large Scale Capacitated Arc Routing Problems with Route Cutting Off Decomposition [article]

Yuzhou Zhang, Yi Mei
2019 arXiv   pre-print
For arc routing, a commonly used divide-and-conquer strategy is to divide the tasks into subsets, and then solve the sub-problems induced by the task subsets separately.  ...  The divide-and-conquer strategy has achieved great success in solving large scale optimization problems by decomposing the original large problem into smaller sub-problems and solving them separately.  ...  As the problem size grows, solving the problem as a whole becomes much less effective, and divide-and-conquer strategy can be a promising technique in this case.  ... 
arXiv:1912.12667v1 fatcat:n4pfmncwqfgdjezxp5sajaoqve

To divide and conquer search ranking by learning query difficulty

Zeyuan Allen Zhu, Weizhu Chen, Tao Wan, Chenguang Zhu, Gang Wang, Zheng Chen
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
Based on this score, our method automatically divides queries into groups, and trains a specific ranking model for each group to conquer search ranking.  ...  In this paper, we demonstrate that it is highly beneficial to divide queries into multiple groups and conquer search ranking based on query difficulty.  ...  We will also use their performance on the entire dataset as the baselines to compare with the divide and conquer technique.  ... 
doi:10.1145/1645953.1646255 dblp:conf/cikm/ZhuCWZWC09 fatcat:46qnzikcavb2ppjdw4pghlcfim

Improving Sales Analysis in Retail Sale using Data Mining Algorithm with Divide and Conquer Method

Myint Myint Yee, University of Computer Studies, Yangon
2018 International Journal of Engineering Research and  
In order to cluster the items, this proposed system will use k-mean clustering algorithm, divide and conquer method.  ...  The advantages of the collection of digitalized data and build data banks has brought in great challenges of data processing for better and meaningful results according to mass data deposits.  ...  We propose an efficient algorithm that is based on divided and conquers techniques for clustering the large sale datasets.  ... 
doi:10.17577/ijertv7is070098 fatcat:wypokxq7fbbivj4bmwrf2i42rq

Divide and conquer

Tyler McDonnell, Sari Andoni, Elmira Bonab, Sheila Cheng, Jun-Hwan Choi, Jimmie Goode, Keith Moore, Gavin Sellers, Jacob Schrum
2018 Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18  
Neuroevolution is a powerful and general technique for evolving the structure and weights of artificial neural networks.  ...  The resulting complete system has proven robust to a wide variety of client datasets.  ...  Divide and Conquer Two divide and conquer based approaches for evolving neural network ensembles are presented.  ... 
doi:10.1145/3205455.3205476 dblp:conf/gecco/McDonnellABCCGM18 fatcat:d5vrinx6mbg3noubbyyzz6cyoi

FP Growth Algorithm Implementation

Shivam Sidhu, Upendra Kumar Meena, Aditya Nawani, Himanshu Gupta, Narina Thakur
2014 International Journal of Computer Applications  
This paper discusses the FP Tree concept and implements it using Java for a general social survey dataset. We use this approach to determine association rules that occur in the dataset.  ...  The Apriori association algorithm is based on pre-computed frequent item sets and it has to scan the entire transaction log / dataset or database which will become a problem with large item sets.  ...  Hence, if the data is too large or complex, the time and complexity are increased. The FP-growth algorithm uses the 'Divide and Conquer' strategy and does not require candidate key generation tests.  ... 
doi:10.5120/16233-5613 fatcat:ptybthxn6nal7ahbttgzn5zd5u

A sampling-based framework for parallel data mining

Shengnan Cong, Jiawei Han, Jay Hoeflinger, David Padua
2005 Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming - PPoPP '05  
In this paper, we present a framework for parallel mining frequent itemsets and sequential patterns based on the divide-and-conquer strategy of pattern growth.  ...  Perhaps the most efficient way to solve these problems sequentially is to apply a pattern-growth algorithm, which is a divide-and-conquer algorithm [9, 10] .  ...  Such divide-and-conquer property is convenient for task partitioning in parallel processing.  ... 
doi:10.1145/1065944.1065979 dblp:conf/ppopp/CongHHP05 fatcat:ap3pc5i4v5cgnfoptszlvrv6u4

Present State-of-The-Art of Association Rule Mining Algorithms

2019 International Journal of Engineering and Advanced Technology  
Association Rule mining is one of the most important techniques of Data Mining, that aims at extracting interesting relationships within the data.  ...  Various functionalities of Data mining include Characterization and Discrimination, Classification and prediction, Association Rule Mining, Cluster analysis, Evolutionary analysis.  ...  and Conquer H-Mine H-Struct Divide and Conquer Patricia mine Particia trie Divide and Conquer RElim Singly Linked List Divide and Conquer PPV PPC tree, Node-list Divide and Conquer Prepost  ... 
doi:10.35940/ijeat.a2202.109119 fatcat:ioaezxalojhljb7nby4icj7wvu

Algorithms Based on Divide and Conquer for Topic-Based Publish/Subscribe Overlay Design

Chen Chen, Hans-Arno Jacobsen, Roman Vitenberg
2016 IEEE/ACM Transactions on Networking  
Inspired by the divide-and-conquer character of this idea, we derive a number of algorithms for the original problem that accommodate a variety of practical pub/sub workloads.  ...  Both theoretical analysis and experimental evaluations demonstrate that our divide-and-conquer algorithms seek a balance between time efficiency and the number of edges required: Our algorithms cost a  ...  DIVIDE-AND-CONQUER FOR - We extend for --to tackle the original problem in a divide-and-conquer manner.  ... 
doi:10.1109/tnet.2014.2369346 fatcat:czl6tcmn4jbvdilyqt7szyilam

Survey on the Techniques of FP-Growth Tree for Efficient Frequent Item-set Mining

Rana Krupali, Dweepna Garg
2017 International Journal of Computer Applications  
FP -Trees pursues the divide and conquers tactic.  ...  Construction and development of classifier that works with more accuracy and performs efficiently for large database is one of the key tasks of data mining techniques.  ...  As in the case of large database its structure fails to fit into main memory hence for this purpose new techniques have been came into existence for reducing dataset and generating tree-structure that  ... 
doi:10.5120/ijca2017912958 fatcat:jmzutttz5vhznlnxoxvblckgc4

Large-Scale Visual Search with Binary Distributed Graph at Alibaba

Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin
2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19  
For a deployed visual search system with several billions of online images in total, building a billion-scale offline graph in hours is essential, which is almost unachievable by most existing methods.  ...  Numbers of methods studying the enhancement of speed and recall have been put forward. However, few of them focus on the efficiency and scale of offline graph-construction.  ...  Single-Pass Divide-And-Conquer Similarly, we take advantage of the divide-and-conquer methodology to build a base approximate neighborhood graph.  ... 
doi:10.1145/3357384.3357834 dblp:conf/cikm/ZhaoPZZWZXJ19 fatcat:yvqezafoz5appoec2a3eelwuqu

Efficient Processing Node Proximity via Random Walk with Restart [chapter]

Bingqing Lv, Weiren Yu, Liping Wang, Julie A. McCann
2014 Lecture Notes in Computer Science  
First, a novel divide-and-conquer paradigm is designed, aiming to convert the large LU decomposition into small triangular matrix operations recursively on several partitioned subgraphs.  ...  However, the best-known algorithm for computing RWR resorts to a large LU matrix factorization on an entire graph, which is cost-inhibitive.  ...  We first devised a divide-and-conquer paradigm to recursively do LU factorization over small subgraphs.  ... 
doi:10.1007/978-3-319-11116-2_50 fatcat:i62cwme5szdg7jh5duk5r6if4i

Large-scale Species Tree Estimation [article]

Erin Molloy, Tandy Warnow
2019 arXiv   pre-print
We also discuss divide-and-conquer strategies for enabling species tree estimation methods to run on large datasets, including new approaches that are based on algorithms (such as TreeMerge) for the Disjoint  ...  In this paper, we review these methods, focusing mainly on issues that relate to analyses of datasets containing large numbers of species or loci (or both).  ...  for scaling species tree estimation methodsHere we describe divide-and-conquer techniques for scaling species tree estimation methods to large datasets.  ... 
arXiv:1904.02600v2 fatcat:6nbf43wiabddhishh445pszsua

Cluster-and-Conquer: When Randomness Meets Graph Locality [article]

George Giakkoupis
2020 arXiv   pre-print
In this paper, we remove this drawback with Cluster-and-Conquer (C 2 for short).  ...  Our extensive evaluation on real datasets shows that Cluster-and-Conquer significantly outperforms existing approaches, including LSH, yielding speed-ups of up to x4.42 while incurring only a negligible  ...  This is hard, as most clustering techniques for item-based datasets either tend to fragment users in a large number of buckets (e.g.  ... 
arXiv:2010.11497v1 fatcat:w3ge474m45cizp6rf2n43nnb4u
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