Content-driven, unsupervised clustering of news articles through multiscale graph partitioning

3 Aug 2018M. Tarik AltuncuSophia N. YalirakiMauricio Barahona

The explosion in the amount of news and journalistic content being generated across the globe, coupled with extended and instantaneous access to information through online media, makes it difficult and time-consuming to monitor news developments and opinion formation in real time. There is an increasing need for tools that can pre-process, analyse and classify raw text to extract interpretable content; specifically, identifying topics and content-driven groupings of articles... (read more)

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