Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 14 of 14 for “"Hierarchical Agglomerative Clustering"”.
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ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
This thesis studies the hierarchical clustering problem, where the goal is to produce a dendrogram that represents clusters at varying scales of a data set. We propose the ParChain framework for designing parallel hierarchical agglomerative clustering (HAC) algorithms, and using the framework we …
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Clustering of Database Query Results
… users information overload can be reduced by clustering database query results. A hierarchical agglomerative clustering algorithm is used to cluster the query results. The reduction of users information overload is evaluated using Chakrabarti et al information overload cost model. Empirical …
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Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa
… the community data aggregated to genus-level. Hierarchical agglomerative clustering reveals two major groups of samples, the mined and the unmined samples.
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Visualisation of Mental Health Community Service Patient Pathways
This research explores the combined use of Clustering and Process Mining techniques to examine patient pathways following referrals to a Community Mental Health Team (CMHT) under Cardiff and Vale University Health Board (CVUHB) for Secondary Mental Health Care. The primary objective is to cluster …
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Experiments in Image Segmentation for Automatic US License Plate Recognition
… techniques applied include multivariate hierarchical agglomerative clustering and minimum-variance color quantization. The trade-off between accuracy and computational expense is used to select a final reliable algorithm for license plate detection and character segmentation. The spectral …
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Comparative structural analysis of cytochrome P450 family CYP51 in the genus Cryptococcus
… (12 CYP51s x 9 ligands =108 complexes) and hierarchical agglomerative clustering were used for selecting the complexes. A web application for visualization of CYP51s’ interactions with ligands was developed (http://bioshell.pl/azoledocking/). The study results indicated that Tremellomycetes …
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On Sequence Clustering and Supervised Dimensionality Reduction
… studies two machine learning problems: 1) clustering of independent and identically generated random sequences, and 2) dimensionality reduction for classification problems. </p> <p>For sequence clustering, the focus is on large sample performance of classical clustering algorithms, …
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Finding functional groups of genes using pairwise relational data : methods and applications
… in modules often have similar gene profiles. Clustering groups of genes with similar profiles can hence deliver candidate gene modules. Pairwise similarity measures derived from these profiles are used as input to the popular hierarchical agglomerative clustering algorithms; however, these …
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The Palaeo-ecology and Biostratigraphy of the foraminifera from the Oxfordian of north Dorset
… authenticity of this method is checked against a Hierarchical Agglomerative Clustering technique. The sample groups are used to define biofacies, fifteen of which are recognised within the studied interval. The correlation of the four boreholes is achieved using lithological techniques, ammonite …
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Routing and Allocation of Unmanned Aerial Vehicles with Communication Considerations
… vehicles. Because of this, a unique approach to clustering is adopted to form clusters using hierarchical agglomerative clustering and fuzzy logic. Based on a detailed Monte Carlo analysis, the heuristic algorithm showed near-optimal (within ~5%) results calculable in real-time (allowing it to be …
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Parallel Algorithms, Optimizations, and Benchmarks for Metric and Graph Clustering
Clustering is a fundamental unsupervised machine learning task of detecting groups of similar objects in data. Clustering can be used to identify the underlying substructures of data and can detect essential functional groups, such as people with similar interests, news articles on similar topics, …
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Bridging Theory and Practice in Parallel Clustering
… and machine learning. In particular, graph clustering, or community detection, is an important problem in graph processing that addresses tangible problems including fraud and threat detection, recommendation and search system design, and the detection of functional contributions of proteins …
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Exploring transcription patterns and regulatory motifs in Arabidopsis thaliana
Recent work has shown that bidirectional genes (genes located on opposite strands of DNA, whose transcription start sites are not more than 1000 basepairs apart) are often co-expressed and have similar biological functions. Identification of such genes can be useful in the process of constructing …
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Statistical issues and developments in time series analysis and educational measurement
… for data generation. Theoretical results on clustering accuracy are given for distance measures used in minimum diameter partitioning and hierarchical agglomerative cluster analysis with complete linkage for data from unidimensional item response models, restricted latent class models for …