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Dissertations / Theses on the topic 'Cluster Computer'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Lindberg, Björn. "Computer availability within a computer cluster." Thesis, University West, Department of Technology, Mathematics and Computer Science, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-532.

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2

Harrison, Mark B. J. "Computer simulation of cluster-cluster aggregation in two dimensions." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266709.

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3

Rosu, Marcel-Catalin. "Communication support for cluster computing." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/8256.

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4

Jiang, Xiaohu 1968. "A scalable parallel inter-cluster communication system for clustered multiprocessors." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43537.

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5

Soares, Rodrigo Gabriel Ferreira. "Cluster-based semi-supervised ensemble learning." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/4818/.

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Semi-supervised classification consists of acquiring knowledge from both labelled and unlabelled data to classify test instances. The cluster assumption represents one of the potential relationships between true classes and data distribution that semi-supervised algorithms assume in order to use unlabelled data. Ensemble algorithms have been widely and successfully employed in both supervised and semi-supervised contexts. In this Thesis, we focus on the cluster assumption to study ensemble learning based on a new cluster regularisation technique for multi-class semi-supervised classification.

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6

Liu, Zhen. "A lightweight intrusion detection system for the cluster environment." Master's thesis, Mississippi State : Mississippi State University, 2003. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07102003-152642/unrestricted/ZhenLiu%5Fthesis.pdf.

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7

Ulmer, Craig D. "Extensible message layers for resource-rich cluster computers." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/13306.

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8

Fang, Weijian. "Distributed object sharing for cluster-based Java virtual machine /." View the Table of Contents & Abstract, 2004. http://sunzi.lib.hku.hk/hkuto/record/B30575163.

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9

Fang, Weijian, and 方維堅. "Distributed object sharing for cluster-based Java virtual machine." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B45014772.

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10

Worm, Stefan. "Monitoring of large-scale Cluster Computers." Master's thesis, Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200700032.

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The constant monitoring of a computer is one of the essentials to be up-to-date about its state. This may seem trivial if one is sitting right in front of it but when monitoring a computer from a certain distance it is not as simple anymore. It gets even more difficult if a large number of computers need to be monitored. Because the process of monitoring always causes some load on the network and the monitored computer itself, it is important to keep these influences as low as possible. Especially for a high-performance cluster that was built from a lot of computers, it is necessary that the m

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11

Zhang, Hua. "VCLUSTER: A PORTABLE VIRTUAL COMPUTING LIBRARY FOR CLUSTER COMPUTING." Doctoral diss., Orlando, Fla. : University of Central Florida, 2008. http://purl.fcla.edu/fcla/etd/CFE0002339.

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12

Worm, Stefan Mehlan Torsten. "Monitoring of large-scale Cluster Computers." [S.l. : s.n.], 2007.

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13

Singla, Aman. "Beehive : application-driven systems support for cluster computing." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/8278.

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14

Marshall, Alisa Marie 1980. "Cluster-based find and replace." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/29696.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.<br>Includes bibliographical references (p. 43).<br>Current Find and Replace tools offer their users only two options when performing a find and replace: replace one match at a time while prompting the user to confirm each replace, or replace all matches at once without any user confirmation. Each of these options can be prone to errors. In this thesis, I investigated, implemented, and tested a third option when performing a find and replace: a cluster-based find and replace. Inst

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15

Lennartsson, Mattias. "Object Recognition with Cluster Matching." Thesis, Linköping University, Department of Electrical Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-51494.

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<p>Within this thesis an algorithm for object recognition called Cluster Matching has been developed, implemented and evaluated. The image information is sampled at arbitrary sample points, instead of interest points, and local image features are extracted. These sample points are used as a compact representation of the image data and can quickly be searched for prior known objects. The algorithm is evaluated on a test set of images and the result is surprisingly reliable and time efficient.</p>

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16

Brolin, Morgan, and Erik Ledin. "Detecting trolls on twitterthrough cluster analysis." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208354.

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The social media platform Twitter is designed to allow users to efficiently spread informationthrough short messages that are broadcast to the world. The efficient way to spreadinformation that is in no way controlled or edited brings inherent problems with the spreadingof misinformation and other malicious activity as it can often be very difficult to establishwhat information can be considered reliable. This study seeks to showcase these problemsas well as find out whether it is possible to identify these malicious users by filtering tweetsby keywords, clustering the tweets based on similari

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17

Bailey, Troy A. "Semiconductor cluster tool availability." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/12020.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994, and Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1994.<br>Includes bibliographical references (p. [131]-133).<br>by Troy A. Bailey.<br>M.S.

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18

Somanathan, Muthuveer. "An initial operating system adaptation heuristic for Swap Cluster Max (SCM)." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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19

Kearns, Brian Patrick. "A Performance Study of LAM and MPICH on an SMP Cluster." PDXScholar, 2002. https://pdxscholar.library.pdx.edu/open_access_etds/2661.

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Many universities and research laboratories have developed low cost clusters, built from Commodity-Off-The-Shelf (COTS) components and running mostly free software. Research has shown that these types of systems are well-equipped to handle many problems requiring parallel processing. The primary components of clusters are hardware, networking, and system software. An important system software consideration for clusters is the choice of the message passing library. MPI (Message Passing Interface) has arguably become the most widely used message passing library on clusters and other parallel arc

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20

Garg, Vikas Ph D. (Vikas Kamur) Massachusetts Institute of Technology. "CRAFT : ClusteR-specific Assorted Feature selecTion." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105697.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 45-46).<br>In this thesis, we present a hierarchical Bayesian framework for clustering with cluster-specific feature selection. We derive a simplified model, CRAFT, by analyzing the asymptotic behavior of the log posterior formulations in a nonparametric MAP-based clustering setting in this framework. The model handles assorted data, i.e., both numeric and categorical data, and the underlying

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21

Nielson, Curtis R. "A Descriptive Performance Model of Small, Low Cost, Diskless Beowulf Clusters." Diss., CLICK HERE for online access, 2003. http://contentdm.lib.byu.edu/ETD/image/etd280.pdf.

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22

譚達俊 and Tat-chun Anthony Tam. "Performance studies of high-speed communication on commodity cluster." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31243642.

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23

Tam, Tat-chun Anthony. "Performance studies of high-speed communication on commodity cluster /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23501753.

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24

何世全 and Sai-chuen Ho. "Single I/O space for scalable cluster computing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31222614.

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25

Ho, Sai-chuen. "Single I/O space for scalable cluster computing /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21841512.

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26

Yu, Weikuan. "Enhancing MPI with modern networking mechanisms in cluster interconnects." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1150470374.

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27

Sit, Yiu-fai, and 薛耀暉. "Cyclone: a high-performance cluster-based webserver with socket cloning." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B29852596.

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28

Ozgencil, Necati Ercan. "Cluster based classification for semantic role labeling." Related electronic resource:, 2007. http://proquest.umi.com/pqdweb?did=1342747481&sid=3&Fmt=2&clientId=3739&RQT=309&VName=PQD.

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29

Lee, Chun-ming, and 李俊明. "Efficient communication subsystem for cluster computing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31221245.

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30

Lee, Chun-ming. "Efficient communication subsystem for cluster computing /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20604592.

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31

Mitchell, Logan Adam. "INCREMENT - Interactive Cluster Refinement." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/5795.

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We present INCREMENT, a cluster refinement algorithm which utilizes user feedback to refine clusterings. INCREMENT is capable of improving clusterings produced by arbitrary clustering algorithms. The initial clustering provided is first sub-clustered to improve query efficiency. A small set of select instances from each of these sub-clusters are presented to a user for labelling. Utilizing the user feedback, INCREMENT trains a feature embedder to map the input features to a new feature space. This space is learned such that spatial distance is inversely correlated with semantic similarity, det

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32

Ramirez, Jon. "Analysis of compute cluster nodes with varying memory hierarchy distributions." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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33

Hendry, Gilbert R. "Applicability of clustering to cyber intrusion detection /." Online version of thesis, 2007. http://hdl.handle.net/1850/4777.

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34

Fellheimer, Eric Todd. "Dynamic load-balancing of StreamIt cluster computations." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36763.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 145-147).<br>This thesis discusses the design and implementation of a dynamic load-balancing mechanism for computationally distributed programs running on a cluster written in the StreamIt programming language. StreamIt is useful for streaming data applications such as MPEG codecs. The structure of the language carries a lot of static information, such as data rates and computational hierarchy, and therefore lends itself well to paralle

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35

Cliffer, Natan Tsvi Cohen. "Decentralized information flow control on a cluster." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/45985.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>Includes bibliographical references (p. 53-54).<br>Information flow control security models can prevent programs from divulging sensitive information in unexpected ways. There has been significant work on tracking information flow between processes in the same computer at the operating system level. I present a modification to the Flume information flow control system for OpenBSD that allows information flow to be tracked between programs on different computers, as long as th

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36

Li, Nan. "Algorithms for NP-hard Optimization Problems and Cluster Analysis." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/482725.

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Computer and Information Science<br>Ph.D.<br>The set cover problem, weighted set cover problem, minimum dominating set problem and minimum weighted dominating set problem are all classical NP-hard optimization problems of great importance in both theory and real applications. Since the exact algorithms, which require exhaustive exploration of exponentially many options, are infeasible in practice, approximation algorithms and heuristic algorithms are widely used to find reasonably good solutions in polynomial time. I propose novel algorithms for these problems. My algorithms for the weighted s

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37

Johnston, Joshua Benjamin Hamerly Gregory James. "Clustering in high dimension and choosing cluster representatives for SimPoint." Waco, Tex. : Baylor University, 2007. http://hdl.handle.net/2104/5067.

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38

Song, Liumeng. "Cluster heads selection and cooperative nodes selection for cluster-based Internet of Things networks." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/24778.

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Clustering and cooperative transmission are the key enablers in power-constrained Internet of Things (IoT) networks. The challenges for power-constrained devices in IoT networks are to reduce the energy consumption and to guarantee the Quality of Service (QoS) provision. In this thesis, optimal node selection algorithms based on clustering and cooperative communication are proposed for different network scenarios, in particular: • The QoS-aware energy efficient cluster heads (CHs) selection algorithm in one-hop capillary networks. This algorithm selects the optimum set of CHs and construct clu

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39

Khan, Masood Mehmood. "Cluster-analytic classification of facial expressions using infrared measurements of facial thermal features." Thesis, University of Huddersfield, 2008. http://eprints.hud.ac.uk/id/eprint/732/.

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In previous research, scientists were able to use transient facial thermal features extracted from Thermal Infra-Red Images (TIRIs) for making binary distinction between the affective states. For example, thermal asymmetries localised in facial TIRIs have been used to distinguish anxiety and deceit. Since affective human-computer interaction would require machines to distinguish between the subtle facial expressions of affective states, computers’ able to make such binary distinctions would not suffice a robust human-computer interaction. This work, for the first time, uses affective-state-spe

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40

Rehmet, Geoffrey Michael. "Remora : implementing adaptive parallelism on a heterogeneous cluster of networked workstations." Thesis, Rhodes University, 1995. http://hdl.handle.net/10962/d1006696.

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Computers connected to a local area network are often only fully utilized for short periods of time. In fact, most workstations are not used at all for a significant portion of the day. The combined "idle time" of the workstations on a network constitutes a significant computing resource, which is generally wasted. If harnessed properly, such a resource could constitute a cheap alternative to expensive high-performance computers. Adaptive parallelism refers to the parallel execution of a computation on a dynamically changing set of processors. This thesis investigates the viability of this app

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41

Eshaftri, Mohamed. "Adaptive energy management mechanisms for cluster based routing wireless sensor networks." Thesis, Edinburgh Napier University, 2017. http://researchrepository.napier.ac.uk/Output/1032654.

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Wireless Sensor Network (WSN) technology has been one of the major avenues of Internet of Things (IoT) due to their potential role in digitising smart physical environments. WSNs are typically composed of a vast number of low-power, low–cost and multifunctional sensor nodes within an area that automatically cooperate to complete the application task. This emerging technology has already contributed to the advancement of a broad range of applications. Nevertheless, the development of WSNs is a challenging issue due to significant concerns, which need to be resolved to take full benefit of this

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42

Tse, Wai-hin Kenneth, and 謝維軒. "Forensic analysis using FAT32 file cluster allocation patterns." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46605733.

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43

Aspegren, Villiam. "CluStic – Automatic graph drawing with clusters." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-179251.

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Finding a visually pleasing layout from a set of vertices and edges is the goal of automatic graph drawing. A requirement that has been barely explored however, is that users would like to specify portions of their layouts that are not altered by such algorithms. For example the user may have put a lot of manual effort into fixing a portion of a large layout and, while they would like an automatic layout applied to most of the layout, they do not want their work undone on the portion they manually fixed earlier. CluStic, the system developed and evaluated in this thesis, provides this capabili

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44

Krantz, Amandus. "Cluster-based Sample Selection for Document Image Binarization." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18433.

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The current state-of-the-art, in terms of performance, for solving document image binarization is training artificial neural networks on pre-labelled ground truth data. As such, it faces the same issues as other, more conventional, classification problems; requiring a large amount of training data. However, unlike those conventional classification problems, document image binarization involves having to either manually craft or estimate the binarized ground truth data, which can be error-prone and time-consuming. This is where sample selection, the act of selecting training samples based on so

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45

Sung, Lik Gan Alex. "Autonomic Resource Management for a Cluster that Executes Batch Jobs." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/1127.

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Resource management of large scale clusters is traditionally done manually. Servers are usually over-provisioned to meet the peak demand of workload. It is widely known that manual provisioning is error-prone and inefficient. These problems can be addressed by the use of autonomic clusters that manage their own resources. In those clusters, server nodes are dynamically allocated based on the system performance goals. In this thesis, we develop heuristic algorithms for the dynamic provisioning of a cluster that executes batch jobs with a shared completion deadline. <br /><br /> Ex

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46

Basak, Debashis. "Designing high performance parallel systems : a processor- cluster based approach /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487935573771706.

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47

Kishimoto, Chikashi. "The Taiwanese personal computer cluster : trajectory of its production and knowledge systems." Thesis, University of Sussex, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394997.

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48

Lin, Dong. "Model-based cluster analysis using Bayesian techniques." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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49

LeBaron, Dean M. "CVIC: Cluster Validation Using Instance-Based Confidences." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5736.

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As unlabeled data becomes increasingly available, the need for robust data mining techniques increases as well. Clustering is a common data mining tool which seeks to find related, independent patterns in data called clusters. The cluster validation problem addresses the question of how well a given clustering fits the data set. We present CVIC (cluster validation using instance-based confidences) which assigns confidence scores to each individual instance, as opposed to more traditional methods which focus on the clusters themselves. CVIC trains supervised learners to recreate the clustering,

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50

Li, Zhen. "CloudVista: a Framework for Interactive Visual Cluster Exploration of Big Data in the Cloud." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1348204863.

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