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Many modern big data applications deal with graph structured data, such as databases of molecular compounds represented as graphs of atoms and bonds, or “structured interaction networks” in biological and social networks, where nodes refer to entities (proteins, people, etc.) and edges represent their relationships. Central to high performance graph analytics over such data, is to locate patterns...
Graph analytics is becoming increasingly popular, with a number of new applications and systems developed in the past few years. In this paper, we study Vertica relational database as a platform for graph analytics. We show that vertex-centric graph analysis can be translated to SQL queries, typically involving table scans and joins, and that modern column-oriented databases are very well suited to...
Explosive increase of real-time data sources, so-called "data streams" (or just "steams") and increasing demands for real-time analysis over streams give rise to realtime analysis over streams. However, developing tailor-made systems for such applications is not always desirable due to high developing costs and long developing periods. To cope with this problem, this paper proposes...
With the continuous increase of heterogeneous multimedia data, the question of how to access big multimedia data efficiently has become of crucial importance. In order to provide fast access to complex multimedia data, we propose to approximate content-based features of multimedia objects by means of generative models. The proposed gradient-based signatures epitomize a high quality content-based approximation...
Every year research institutions produce petabytes of data. Yet, only a small percent of the data is readily accessible for analysis. Terra Populus acts as the bridge between big data sources and researchers. Researchers are provided convenient web applications that allow them to access, analyze, and tabulate different datasets under a common platform. Terra Populus is developing three unique applications...
In the era of data-intensive scientific discovery, data analysis is critical for scientists to identify essential information from the mountains of data generated by large-scale simulations or experiments. A generic operation in scientific data analysis is to combine information from multiple data sets, which are stored in heterogeneous ile formats. This operation is typically known as a Join in database...
With the development of various Cloud platforms, providing spatio-temporal database services is an essential requirement for many applications, e.g., location-based services in Cloud. However, many previous works on processing queries in distributed environment fail to apply to spatio-temporal queries which is a significant role in spatio-temporal database. In this paper, we propose an efficient and...
There exist large datasets containing the sequences of points that moving objects occupy in space as time goes by. Such sequences of moving objects are known as trajectories. Being able to issue queries that allow the extraction of patterns from the movements of these objects is important to many real world applications, such as urban planning in transportation and bird migration tracking in ecology...
The number of linked data sources and the size of the linked open data graph keep growing every day. As a consequence, semantic RDF services are more and more confronted with various "big data" problems. Query processing in the presence of inferences is one them. For instance, to complete the answer set of SPARQL queries, RDF database systems evaluate semantic RDFS relationships (subPropertyOf,...
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