Very Large Databases
Database machines in support of very large databases
... Table of Contents-2 Multiple Hosts 1-14 Vulnerability 1-14 Other Features 1-14 Architectural Overview 1-16 Host System Communications Interface Interface Processor IFP Ynet Access Module[r] ...
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Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation
... Extensions and generalization. Two works [4,14] showed that data structures for single-keyword SSE can be generalized to work for more complex SSE functionalities and models. Specifically, [4] shows how to extend SSE ...
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Effects of Album and Artist Filters in Audio Similarity Computed for Very Large Music Databases
... There clearly is both an album and an artist effect in music recommendation even in very large databases. For the timbre based method G1, about one third of the first recommendations are from the ...
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Scaling associative classification for very large datasets
... Attempts to bring the training of an associative classifier onto a framework for paral- lel computing and scale to large datasets have been done in [4, 5]. The authors of [4] proposed a MapReduce solution based on ...
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Finding community structure in very large networks
... We have described a new algorithm for inferring com- munity structure from network topology which works by greedily optimizing the modularity. Our algorithm runs in time O(md log n) for a network with n vertices and m ...
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Fangorn: A System for Querying very large Treebanks
... The efficiency and robustness of statistical parsers has made it possible to create very large treebanks. These serve as the starting point for further work including enrichment, extraction, and curation: ...
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Risamálheild: A Very Large Icelandic Text Corpus
... A pragmatic approach to text collection was adopted. Texts requiring a minimum of cleaning and processing and texts accompanied by relevant metadata were preferred. This applied to texts obtained from databases of ...
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Towards Understanding Text with a Very Large Vocabulary
... Towards Understanding Text with a Very Large Vocabulary Towards Understanding Text with a Very Large Vocabulary Damaris Ayuso, R Bobrow, Dawn MacLaughlin, Marie Meteer, Lance Ramshaw, Rich Schwartz, R[.] ...
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A Survey of Clustering Algorithm for Very Large Datasets
... In the paper given by “Tian Zhang ,Raghu Ramakrishnan ,Miron Livny ” in “BIRCH: A New Data Clustering Algorithm and Its Applications ” the author (propose a birch method for large database) BIRCH creates a height ...
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Indexing for Very Large Data Series Collections
... One of the simplest ways to evaluate similarity search queries, is that of performing a serial scan over the data series. Data series can either be in their raw form, or trans- formed using wavelets or Fourier ...
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Visualization Databases for the Analysis of Large Complex Datasets
... a large complex dataset re- quires a visualization database (VDB): many displays, some with many pages, and with one or more panels per ...a large sample over a small ...
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A Very Very Large Corpus Doesn’t Always Yield Reliable Estimates
... seen very rarely, until it suddenly becomes very popu- ...a very high initial estimate in Figure ...the very beginning of the corpus, but did not appear in the remainder of the ...by ...
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Speckle Imaging with the SOAR and the Very Large Telescopes
... Astronomical speckle imaging is a well established technique for obtaining diffraction limited images of binary and multiple stars, low contrast solar features and nearby extended objects such as comets and solar system ...
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Next Generation Very Large Array Memo No.??
... generation Very Large Array – an interferometric array with 10 times greater effective collecting area and spatial resolution than the current VLA and ALMA, optimized for operation in the ...Generation ...
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Large-scale spatial population databases in infectious disease research
... Among the agents involved in the disease transmission process, human hosts play a crucial role as their density [26], spatial location, demographic characteristics (e.g. age-risk profiles [27-30]) and behaviour [31-33] ...
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A MATRIX MODEL FOR MINING FREQUENT PATTERNS IN LARGE DATABASES
... Data mining has been recognized as promising field of database research due to its wide and significant applications in industry. It is a key step in the knowledge discovery process in large databases (Han ...
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D-GridMST: clustering large distributed spatial databases
... with large distributed spatial ...spatial databases, based on which a global MST of representatives is ...spatial databases is transferred via network, D-GridMST is characterized by small network ...
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Exploring the value of large databases of transaction data for business intelligence
... Secondary data is used in this study, which means the case did not gather the data for the immediate study at hand but for other purposes. Primary data, in contrast, are originated by the researcher for the purpose of ...
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An Effective Approach in Data Mining to Reduce Redundancies in Large Databases
... With the increased dissemination of bar code scanning technologies it was possible to accumulate vast amounts of Market-basket dataset containing millions of transactions. Thus the need arose to study the patterns of ...
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Challenges in the automated classification of variable stars in large databases
... Abstract. With ever-increasing numbers of astrophysical transient surveys, new facili- ties and archives of astronomical time series, time domain astronomy is emerging as a mainstream discipline. However, the sheer ...
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