Detail výsledku
Collective Intelligence Generation from User Contributed Content
Mylonas Phivos
Geyer-Schultz Andreas
Hoser Betina
Chapman Sam
Ciravenga Fabio
Lanfranchi Vita
Scherp Ansgar
Staab Stefen
Contopoulos Costis
Gkika Ioanna
Bakaimis Byron
Smrž Pavel, doc. RNDr., Ph.D., UPGM (FIT)
Kompatsiaris Yiannis
Avrithis Yannis
In this paper we provide a foundation for a new generation of
services and tools. We define new ways of capturing, sharing and
reusing information and intelligence provided by single users and
communities, as well as organizations by enabling the extraction,
generation, interpretation and management of Collective
Intelligence from user generated digital multimedia content.
Different layers of intelligence are generated, which together
constitute the notion of Collective Intelligence.
The automatic generation of Collective Intelligence
constitutes a departure from traditional methods for information
sharing, since information from both the multimedia content and
social aspects will be merged, while at the same time the social
dynamics will be taken into account. In the context of this work,
we present two case studies an Emergency
Response and a Consumers Social Group case
study.
Collective intelligence, media intelligence, social intelligence,
mass intelligence, organizational intelligence, personal intelligence
@inbook{BUT55770,
author="Vassilios {Solachidis} and Phivos {Mylonas} and Andreas {Geyer-Schultz} and Betina {Hoser} and Sam {Chapman} and Fabio {Ciravenga} and Vita {Lanfranchi} and Ansgar {Scherp} and Stefen {Staab} and Costis {Contopoulos} and Ioanna {Gkika} and Byron {Bakaimis} and Pavel {Smrž} and Yiannis {Kompatsiaris} and Yannis {Avrithis}",
title="Collective Intelligence Generation from User Contributed Content",
booktitle="Advances in Data Analysis, Data Handling and Business Intelligence",
year="2010",
publisher="Springer Verlag",
address="Berlin",
series="Studies in Classification, Data Analysis, and Knowledge Organization",
pages="765--774",
isbn="978-3-642-01043-9"
}