Algorithms and Architectures for Parallel Processing
ICA3PP 2016 Collocated Workshops: SCDT, TAPEMS, BigTrust, UCER, DLMCS, Granada, Spain, December 14-16, 2016, Proceedings
Chapter
MapReduce is a programming model widely used in Cloud computing environments for processing large data sets in a highly parallel way. MapReduce implementations are based on a master-slave model. The failure of...
Chapter and Conference Paper
The advent of Cloud computing has given to researchers the ability to access resources that satisfy their growing needs, which could not be satisfied by traditional computing resources such as PCs and locally ...
Chapter and Conference Paper
Cloud platforms provide scalable processing and data storage and access services that can be exploited for implementing high-performance knowledge discovery systems and applications. This paper discusses the u...
Article
The rise of virtualized and distributed infrastructures has led to new challenges to accomplish the effective use of compute resources through the design and orchestration of distributed applications. As legac...
Book and Conference Proceedings
ICA3PP 2016 Collocated Workshops: SCDT, TAPEMS, BigTrust, UCER, DLMCS, Granada, Spain, December 14-16, 2016, Proceedings
Chapter and Conference Paper
A core functionality of any location-aware ubiquitous system is storing, indexing, and retrieving information about entities that are commonly involved in these scenarios, such as users, places, events and oth...
Article
The Data Mining Cloud Framework (DMCF) is an environment for designing and executing data analysis workflows in cloud platforms. Currently, DMCF relies on the default storage of the public cloud provider for a...
Chapter
MapReduce is one of the most popular programming models for parallel data processing in Cloud environments. Standard MapReduce implementations are based on centralized master-slave architectures that do not co...
Chapter
The huge amount of data generated, the speed at which it is produced, and its heterogeneity in terms of format, represent a challenge to the current storage, process and analysis capabilities. Those data volum...
Article
Social media analysis is a fast growing research area aimed at extracting useful information from social networks. Recent years have seen a great interest from academic and business world in using social media...
Chapter and Conference Paper
Software systems for social media analysis provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a Java library for dev...
Article
Software systems for social data mining provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a high-level library for ...
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Reference Work Entry In depth
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Social media analysis is a fast growing research area aimed at extracting useful information from social media. Several opinion mining techniques have been developed for capturing the mood of social media user...
Chapter and Conference Paper
In recent years, the demand for collective mobility services is characterized by a significant growth. The long-distance coach market has undergone an important change in Europe since FlixBus adopted a dynamic...
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This paper presents the main features and the programming constructs of the DCEx programming model designed for the implementation of data-centric large-scale parallel applications on Exascale computing platforms...
Chapter and Conference Paper
Every day billions of people access web sites, blogs, and social media. Often they use their mobile devices and produce huge amount of data that can be effectively exploited for extracting valuable information...
Article
Social media platforms have become fundamental tools for sharing information during natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events Detection on sOcial Media During Disasters...
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