An architecture for processing of heterogeneous sources

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.