In this paper we propose to integrate Time-Aware Fuzzy Formal Concept Analysis theory with OLAP technology over multidimensional tweet streams in order to arrange tweets in the resulting OLAP cube within a suitable hierarchical structure of concepts (i.e., fuzzy lattice), according to their unstructured content. A microblog summarization algorithm is also introduced in order to provide subset of the tweets that best represents data of the OLAP cube according to the analysis perspective. This with the final goal of supporting advanced analytics over social media, which is becoming relevant at now. A detailed real-life and an extensive experimental analysis nicely complete our contributions.

OLAP analysis of multidimensional tweet streams for supporting advanced analytics

CUZZOCREA, ALFREDO;FENZA, GIUSEPPE;DE MAIO, CARMEN;LOIA, Vincenzo;PARENTE, Domenico
2016-01-01

Abstract

In this paper we propose to integrate Time-Aware Fuzzy Formal Concept Analysis theory with OLAP technology over multidimensional tweet streams in order to arrange tweets in the resulting OLAP cube within a suitable hierarchical structure of concepts (i.e., fuzzy lattice), according to their unstructured content. A microblog summarization algorithm is also introduced in order to provide subset of the tweets that best represents data of the OLAP cube according to the analysis perspective. This with the final goal of supporting advanced analytics over social media, which is becoming relevant at now. A detailed real-life and an extensive experimental analysis nicely complete our contributions.
2016
9781450337397
9781450337397
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4670373
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