Microblog service has attracted much attention in big data analysis. Twitter statistics remark that the average number of tweets per day is greater than 100 million and many thousands of them happen every minute. It's an urgent challenge to face with such a large amount of collected tweets. This work defines an online query-focused Twitter summarization framework. It crawls and semantically indexes tweets exploiting wikification service. When a user's query is submitted, the system filters out the most relevant tweets. Then, a summarization algorithm browses the knowledge structure extracted by performing a Fuzzy Formal Concept Analysis on the given filtered tweets. Experimental results reveal good performances.

Online query-focused twitter summarizer through fuzzy lattice

DE MAIO, CARMEN;FENZA, GIUSEPPE;LOIA, Vincenzo;PARENTE, Domenico
2015

Abstract

Microblog service has attracted much attention in big data analysis. Twitter statistics remark that the average number of tweets per day is greater than 100 million and many thousands of them happen every minute. It's an urgent challenge to face with such a large amount of collected tweets. This work defines an online query-focused Twitter summarization framework. It crawls and semantically indexes tweets exploiting wikification service. When a user's query is submitted, the system filters out the most relevant tweets. Then, a summarization algorithm browses the knowledge structure extracted by performing a Fuzzy Formal Concept Analysis on the given filtered tweets. Experimental results reveal good performances.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4655210
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