In the Web 2.0, where everyone is the creator of content, information spreads and evolves rapidly through unpredictable paths of rebounds between news sources and Social Media. In this context, mod- eling, analyzing and tracking the information evolution through time offers unprecedented opportunities to diverse research fields, including Information Retrieval. In this paper we propose a synthetic analysis of the state-of-Art on Information Evolution on theWeb, and we summarize the interesting opportunities it offers to Information Retrieval.
Shabunina, E., Pasi, G. (2017). Information evolution modeling and tracking: State-of-Art, challenges and opportunities. In Proceedings of the 8th Italian Information Retrieval Workshop (pp.102-105). CEUR-WS.
Information evolution modeling and tracking: State-of-Art, challenges and opportunities
Shabunina, Ekaterina
Primo
;Pasi, GabriellaSecondo
2017
Abstract
In the Web 2.0, where everyone is the creator of content, information spreads and evolves rapidly through unpredictable paths of rebounds between news sources and Social Media. In this context, mod- eling, analyzing and tracking the information evolution through time offers unprecedented opportunities to diverse research fields, including Information Retrieval. In this paper we propose a synthetic analysis of the state-of-Art on Information Evolution on theWeb, and we summarize the interesting opportunities it offers to Information Retrieval.
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