Scalable Knowledge Extraction and Visualization for Web Intelligence

Citation

[scharl2016, self.bib] Scharl, Arno, Weichselbraun, Albert, Göbel, Max, Rafelsberger, Walter and Kamolov, Ruslan (2016). ''Scalable Knowledge Extraction and Visualization for Web Intelligence'', Proceedings of the 49th Hawaii International Conference on System Sciences (HICSS-49), IEEE Computer Society Press

Abstract

Understanding stakeholder perceptions and assessing the impact of campaigns are key questions of communication experts. Web intelligence platforms help to answer such questions, provided that they are scalable enough to analyze and visualize information flows from volatile online sources in real time. This paper presents a distributed architecture for aggregating Web content repositories from Web sites and social media streams, memory-efficient methods to extract factual and affective knowledge, and interactive visualization techniques to explore the extracted knowledge. The presented examples stem from the Media Watch on Climate Change, a public Web portal that aggregates environmental content from a range of online sources.

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