Title :
Exploratory analysis of large web datasets
Author :
Silvana Castano;Alfio Ferrara;Stefano Montanelli
Author_Institution :
Department of Computer Science, Università
Abstract :
In the era of big data, the capability to identify very quickly prominent summary information about a target entity of interest, like a person or an event, from large datasets is essential, and exploratory analysis techniques help in this direction. In this paper, we provide a solution based on smart entity views and on pre-defined analysis operators which exploit keywords available in the entity view together with similarity information to produce summary information about the view contents from both a thematic and analytics perspective. In particular, smart entity views can be analyzed according to the following exploratory paradigms: entity expansion, entity visualization, and entity analytics. The proposed approach is discussed by referring to a case study of twitter dataset related to the “Expo2015” event as target entity.
Keywords :
"Correlation","Information services","Chlorine","Clustering algorithms","Twitter","Visualization","Tagging"
Conference_Titel :
Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), 2015 IEEE 1st International Forum on
DOI :
10.1109/RTSI.2015.7325105