S.G. Lade, Nikhil Vyawahare
Real-time and archrival data documents are increases as fast as or faster than computing power now a days. Document classification using k-nn classification algorithm takes more time in searching nearer neighbors in large training dataset, it include large number of computations. The time for classification increases in proportion to the number of documents. Therefore it […]
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Glen Hordemann
This thesis introduces the development of a new GPU-based database to accelerate queries of Digital Humanities data to extract document texts that are then data-mined to produce visualizations of aspects of the humanities data. The goal is to advance the state-of-the-art in massively parallel database work by investigating methods for utilizing graphical processing units in […]
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Peter Wittek, Sandor Daranyi
Scientific computations have been using GPU-enabled computers successfully, often relying on distributed nodes to overcome the limitations of device memory. Only a handful of text mining applications benefit from such infrastructure. Since the initial steps of text mining are typically data intensive, and the ease of deployment of algorithms is an important factor in developing […]
Peter Wittek
Somoclu is a C++ tool for training self-organizing maps on large data sets using a high-performance cluster. It builds on MPI for distributing the workload across the nodes of the cluster. It is also able to boost training by using CUDA if graphics processing units are available. A sparse kernel is included, which is useful […]
Jason P. Duran, Sathish AP Kumar
This paper introduces a Multi Objective Parallel Genetic Algorithm (MOPGA) using the Compute Unified Device Architecture (CUDA) hardware for parallel processing. The algorithm demonstrates significant speed gains using affordable, scalable and commercially available hardware. The algorithm implements a document search using techniques such as Term Frequency Inverse Document Frequency (TF-IDF), Latent Semantic Analysis (LSA), Multi […]
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Volodymyr Kysenko, Karl Rupp, Oleksandr Marchenko, Siegfried Selberherr, Anatoly Anisimov
An implementation of the non-negative matrix factorization algorithm for the purpose of text mining on graphics processing units is presented. Performance gains of more than one order of magnitude are obtained.
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Xiwu Gu, Ruixuan Li, Kunmei Wen, Bei Peng, Weijun Xiao
The task of Chinese word segmentation is to split sequence of Chinese characters into tokens so that the Chinese information can be more easily retrieved by web search engine. Due to the dramatic increase in the amount of Chinese literature in recent years, it becomes a big challenge for web search engines to analyze massive […]
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Peter Wittek, Sandor Daranyi
With the emergence of high-performance computing instances in the cloud, massive scale computations have become available to technically every organization. Digital libraries typically employ a data-intensive infrastructure, but given the resources, advanced services based on data and text mining could be developed. A fundamental issue is the ease of development and integration of such services. […]
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Youngmin Yi, Chao-Yue Lai, Slav Petrov, Kurt Keutzer
Low-latency solutions for syntactic parsing are needed if parsing is to become an integral part of user-facing natural language applications. Unfortunately, most state-of-the-art constituency parsers employ large probabilistic context-free grammars for disambiguation, which renders them impractical for real-time use. Meanwhile, Graphics Processor Units (GPUs) have become widely available, offering the opportunity to alleviate this bottleneck […]
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Hang Chen
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining tasks such as retrieval, clustering, summarization, etc. PLSA involves iterative computation for a large number of parameters and may take hours or even days to process a large dataset, thus speeding up PLSA is highly motivated in the domain of text mining. […]
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Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok
Accelerating hardware devices represent a novel promise for im- proving the performance for many problem domains but it is not clear for which domains what accelerators are suitable. While there is no room in general-purpose processor design to significantly in- crease the processor frequency, developers are instead resorting to multi-core chips duplicating conventional computing capabilities […]
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M. D. Lieberman, J. Sankaranarayanan, H. Samet
A similarity join operation A BOWTIE_epsiv B takes two sets of points A, B and a value epsiv isin Ropf, and outputs pairs of points p in A,q in B, such that the distance D(p,q) < epsiv. Similarity joins find use in a variety of fields, such as clustering, text mining, and multimedia databases. A […]
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