Different sources of information generate every day huge amount of data. For example, let us consider social networks: here the number of active users is impressive; they process and publish information in different formats and data are heterogeneous in their topics and in the published media (text, video, images, audio, etc.). In this work, we present a general framework for event detection in processing of heterogeneous data from social networks. The framework we propose, implements some techniques that users can exploit for malicious events detection on Twitter. © Springer International Publishing AG 2017.
An architecture for processing of heterogeneous sources / Amato, F.; Cozzolino, G.; Mazzeo, A.; Romano, S.. - 1:(2017), pp. 679-688. [10.1007/978-3-319-49109-7_65]
An architecture for processing of heterogeneous sources
Amato, F.
;Cozzolino, G.;Mazzeo, A.;Romano, S.
2017
Abstract
Different sources of information generate every day huge amount of data. For example, let us consider social networks: here the number of active users is impressive; they process and publish information in different formats and data are heterogeneous in their topics and in the published media (text, video, images, audio, etc.). In this work, we present a general framework for event detection in processing of heterogeneous data from social networks. The framework we propose, implements some techniques that users can exploit for malicious events detection on Twitter. © Springer International Publishing AG 2017.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
