Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Clustering of Social Tagging System Users: A Topic and Time Based Approach
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Bridging the Gap between Desktop and the Cloud for eScience Applications
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Identifying, attributing and describing spatial bursts
Proceedings of the VLDB Endowment
Towards transparent integration of heterogeneous cloud storage platforms
Proceedings of the fourth international workshop on Data-intensive distributed computing
Capturing Social Data Evolution Using Graph Clustering
IEEE Internet Computing
Evolving social data mining and affective analysis methodologies, framework and applications
Proceedings of the 16th International Database Engineering & Applications Sysmposium
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Social networking media generate huge content streams, which leverage, both academia and developers efforts in providing unbiased, powerful indications of users' opinion and interests. Here, we present Cloud4Trends, a framework for collecting and analyzing user generated content through microblogging and blogging applications, both separately and jointly, focused on certain geographical areas, towards the identification of the most significant topics using trend analysis techniques. The cloud computing paradigm appears to offer a significant benefit in order to make such applications viable considering that the massive data sizes produced daily impose the need of a scalable and powerful infrastructure. Cloud4Trends constitutes an efficient Cloud-based approach in order to solve the online trend tracking problem based on Web 2.0 sources. A detailed system architecture model is also proposed, which is largely based on a set of service modules developed within the VENUS-C research project to facilitate the deployment of research applications on Cloud infrastructures.