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 20 of 74 for “"massive data"”.
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Sublinear algorithms for massive data problems
… problems in the models that address massive data sets. The models include streaming algorithms, sublinear time algorithms, property testing algorithms, sublinear query time algorithms with preprocessing, or computing small summaries for large data. More precisely, we study the …
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Practical methods for data mining with massive data sets
The increasing size of data sets has necessitated advancement in exploratory techniques. Methods that are practical for moderate to small data sets become infeasible when applied to massive data sets. Advanced techniques such as binned kernel density estimation, tours, and mode-based projection …
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Functional testing techniques for new massive data processing paradigms
Los programas Big Data son aquellos que analizan información utilizando nuevos modelos de procesamiento que superan las limitaciones de la tecnología tradicional en cuanto al volumen, velocidad y variedad de los datos procesados. Entre estos, se destaca MapReduce que permite procesar grandes …
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Massive data visualization based on dimensionality reduction and projection error evaluation /
… thesis two ways to evaluate projection error for massive data sets are proposed. One of them is based on building the sample of the data set, the second one on dividing the data set into the smaller data sets. Both proposed ways of projection error evaluation are suitable for massive data sets and …
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Algorithms for data mining
Data of massive size are now available in a wide variety of fields and come with great promise. In theory, these massive data sets allow data mining and exploration on a scale previously unimaginable. However, in practice, it can be difficult to apply classic data mining techniques to such massive …
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Dimensijų mažinimu pagrįstas didelės apimties duomenų vizualizavimas ir projekcijos paklaidos vertinimas /
… thesis two ways to evaluate projection error for massive data sets are proposed. One of them is based on building the sample of the data set, the second one on dividing the data set into the smaller data sets. Both proposed ways of projection error evaluation are suitable for massive data sets and …
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Efficient algorithms for new computational models
… balancing and for locality-aware distributed data storage in peer-to-peer networks. The last model is based on extensions of the streaming model. It is an attempt to capture the class of problems that can be efficiently solved on massive data sets. We give a number of algorithms for this …
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Sequential nonparametric estimation via Hermite series estimators
… the statistical properties of streams of data in real time, as well as for the efficient analysis of massive data sets, are becoming particularly pertinent given the increasing ubiquity of such data. In this thesis we introduce novel approaches to sequential (online) estimation in both …
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Hierarchical Bayesian Analysis of Peruvian Tree Growth Rates
… and hierarchical modeling in order to analyze massive data sets of Peruvian tree growth data. The study is important in finding connections between different parameters (such as the tree's classification or elevation) and rate at which the tree grows. We combine the Bayesian paradigm with the …
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Multi-scale data sketching for large data analysis and visualization
<p>Analysis and visualization of large data sets is time consuming and sometimes can be a very difficult process, especially for 3D data sets. Therefore, data processing and visualization techniques have often been used in the case of different massive data analysis for efficiency and accuracy …
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Visualizing remixes in an online programming community
… usable and visually appealing tree which handles massive data sets fairly well, but continues to require iteration.
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A Framework for the Design and Generation of Spatial MFSA Accelerators: The SPARX Approach
… computational overhead when evaluated over massive data streams. Traditional CPU and GPU solutions, despite vectorization and multi-threading, remain constrained by the sequential execution model of Von Neumann architectures. This thesis addresses these limitations by introducing SPARX, the …
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Memory access patterns and page promotion in hybrid memory systems
… performance and energy walls in processing data-intensive applications, which are becoming the norm with the resurgence of machine learning, big data, graph analytics, and database management systems, especially in modern datacenters. In addition to the massive data that these applications …
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Locality-aware cache hierarchy management for multicore processors
… processors and applications will operate on massive data with significant sharing. A major challenge in their implementation is the storage requirement for tracking the sharers of data. The bit overhead for such storage scales quadratically with the number of cores in conventional …
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Template B+ trees: an index scheme for fast data streams with distributed append-only stores
… systems are now commonly used to manage massive data flooding from the physical world, such as user-generated content from online social media and communication records from mobile phones. The new generation of distributed data management systems, such as HBase, Cassandra and Riak, are …
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Development of vertical cavity transistor laser and microcavity laser
… semiconductor laser is of great interest for the massive data transmission demands in butt computing servers and supercomputing technologies. Currently, commercial vertical-cavity surface-emitting diode lasers (VCSELs) have achieved a data transmission rate of 25 Gbit/s per channel. However, the …
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CyberVisual : designing user environments for large scale networks and simulations
The growth of data collection within the technology sector has been increasing at an astounding rate over the last decade. This growth has given rise to techniques and statistical tools for computation that enable us to see trends and answer queries; however, most of this information has been in …
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Statistical analysis of networks with community structure and bootstrap methods for big data
… dissertation concerns bootstrap methods for big data. Statistical analysis of networks with community structure: Networks are ubiquitous in today's world --- network data appears from varied fields such as scientific studies, sociology, technology, social media and the Internet, to name a few. An …
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Spatial provenance: A case study on geological carbon sequestration
… information derived from the handling of spatial data—spatial provenance—requires effective management of transformational workflows and associated metadata for workflow components. The spatial provenance model presented in this thesis captures important information for understanding spatial data …
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Cloud computing for digital libraries
… S3) to store large and increasing volumes of data, Amazon Elastic Compute Cloud (Amazon EC2) to provide the required computational power and Amazon SimpleDB for querying and data indexing on Amazon S3. A proof-of-concept application comprising typical digital library services was developed and …
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