Related papers: Spatial Indexing of Large Multidimensional Databas…
Apache Spark is a Big Data framework for working on large distributed datasets. Although widely used in the industry, it remains rather limited in the academic community or often restricted to software engineers. The goal of this paper is…
Data series similarity search is a core operation for several data series analysis applications across many different domains. However, the state-of-the-art techniques fail to deliver the time performance required for interactive…
Data warehouse store and provide access to large volume of historical data supporting the strategic decisions of organisations. Data warehouse is based on a multidimensional model which allow to express user's needs for supporting the…
Digital world is growing very fast and become more complex in the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), velocity (high speed in growth) in nature. This refers to as Big Data that is a global…
The Sloan Digital Sky Survey (SDSS) is making a multi-colour, three dimensional map of the nearby Universe. The survey is in two parts. The first part is imaging one quarter of the sky in five colours from the near ultraviolet to the near…
A set of preferred records can be obtained from a large database in a multi-criteria setting using various computational methods which either depend on the concept of dominance or on the concept of utility or scoring function based on the…
The data volumes stored in telescope archives is constantly increasing due to the development and improvements in the instrumentation. Often the archives need to be stored over a distributed storage architecture, provided by independent…
The primary observational goals of the Sloan Digital Sky Survey are to obtain CCD imaging of 10,000 deg^2 of the north Galactic cap in five passbands, with a limiting magnitude in the r-band of 22.5, to obtain spectroscopic redshifts of…
The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity…
Multidimensional databases support efficiently on-line analytical processing (OLAP). In this paper, we depict a model dedicated to multidimensional databases. The approach we present designs decisional information through a constellation of…
Spatial data fusion is a bottleneck when it meets the scale of 10 billion records. Cross-matching celestial catalogs is just one example of this. To challenge this, we present a framework that enables efficient cross-matching using Learned…
The Sloan Digital Sky Survey (SDSS) is collecting photometry and intermediate resolution spectra for ~ 10**5 stars in the thick-disk and stellar halo of the Milky Way. This massive dataset can be used to infer the properties of the stars…
Advanced instruments in a variety of scientific domains are collecting massive amounts of data that must be post-processed and organized to support scientific research activities. Astronomers have been pioneers in the use of databases to…
Astronomy is increasingly encountering two fundamental truths: (1) The field is faced with the task of extracting useful information from extremely large, complex, and high dimensional datasets; (2) The techniques of astroinformatics and…
As more data-intensive applications emerge, advanced retrieval semantics, such as ranking or skylines, have attracted attention. Geographic information systems are such an application with massive spatial data. Our goal is to efficiently…
Astronomy is entering a new era as multiple, large area, digital sky surveys are in production. The resulting datasets are truly remarkable in their own right; however, a revolutionary step arises in the aggregation of complimentary…
One of important aims of astronomical data mining is to systematically search for specific rare objects in a massive spectral dataset, given a small fraction of identified samples with the same type. Most existing methods are mainly based…
Many industries rely on visual insights to support decision- making processes in their businesses. In mining, the analysis of drills and geological shapes, represented as 3D geometries, is an important tool to assist geologists on the…
Large databases are often organized by hand-labeled metadata, or criteria, which are expensive to collect. We can use unsupervised learning to model database variation, but these models are often high dimensional, complex to parameterize,…
With the rise of GPS-enabled smartphones and other similar mobile devices, massive amounts of location data are available. However, no scalable solutions for soft real-time spatial queries on large sets of moving objects have yet emerged.…