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Emerging, collective intelligence for personal, organizational and social use

Description du projet


Intelligent Content and Semantics

Novel techniques for generating different layers of intelligence


WeKnowIt aims to develop techniques for exploiting multiple layers of intelligence from user-contributed content, which together constitute Collective Intelligence. The project will provide technology able to support a paradigm shift, establishing a foundation for a new generation of services and tools supporting communities of users. The approach is built around different Intelligence Layers (Personal, Media, Mass, Social and Organisational) which address various aspects of user contributed and consumed content. The emphasis will be on integration and bridging (e.g. social and content dimensions) and the mobile and organisational – business aspects. WeKnowIt will demonstrate the wide applicability of its achievements through the elaboration on two distinct case studies: an Emergency response and a Consumers Social Group case study.

Due to advances in communications, mobile devices and Web technologies, it is nowadays easy for users and organizations to generate and share content, individually or within communities. However, such digital content rapidly reaches a mass that makes relevant information extremely complex and costly to handle. Yet, current applications do not fully support intelligent processing and management of such information. Thus, users fail to access it efficiently and cannot exploit the underlying knowledge.
The main objective of WeKnowIt is to develop novel techniques for exploiting multiple layers of intelligence from user-contributed content, which together constitute Collective Intelligence, a form of intelligence that emerges from the collaboration and competition among many individuals, and that seemingly has a mind of its own. To this end, input from various sources is analysed and combined: from digital content items and contextual information (Media Intelligence), massive user feedback (Mass Intelligence), and users social interaction (Social Intelligence) so as to benefit end-users (Personal Intelligence) and organizations (Organisational Intelligence).
The automatic generation of Collective Intelligence constitutes a departure from traditional methods for information sharing, since for example, semantic analysis has to fuse information from both the content itself and the social context, while at the same time the social dynamics have to be taken into account. Such intelligence provides added-value to the available content and renders existing procedures and workflows more efficient.
WeKnowIt will demonstrate the wide applicability of its achievements through the elaboration on two distinct case studies: an Emergency Response and a Consumers Social Group case study. The two use cases pertain to different topics, target at a wide range of intended users and involve heterogeneous business models so that WeKnowIt achieves the highest possible social impact.

Appel à propositions

FP7-ICT-2007-1
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Coordinateur

ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS
Contribution de l’UE
€ 1 198 716,00
Adresse
CHARILAOU THERMI ROAD 6 KM
57001 Thermi Thessaloniki
Grèce

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Région
Βόρεια Ελλάδα Κεντρική Μακεδονία Θεσσαλονίκη
Type d’activité
Research Organisations
Contact administratif
Konstantinos Kiparissides (Prof)
Liens
Coût total
Aucune donnée

Participants (12)