Collective intelligence system engineering

Lykourentzou, I; Vergados, DJ; Loumos, V

dc.contributor.author	Lykourentzou, I	en
dc.contributor.author	Vergados, DJ	en
dc.contributor.author	Loumos, V	en
dc.date.accessioned	2014-03-01T02:46:03Z
dc.date.available	2014-03-01T02:46:03Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32509
dc.subject	Collective intelligence	en
dc.subject	System engineering	en
dc.subject.other	Collective intelligences	en
dc.subject.other	Design and construction	en
dc.subject.other	Key issues	en
dc.subject.other	Large groups	en
dc.subject.other	Machine intelligence	en
dc.subject.other	Modeling frameworks	en
dc.subject.other	Research fields	en
dc.subject.other	System state	en
dc.subject.other	User action	en
dc.subject.other	User communities	en
dc.subject.other	Web users	en
dc.subject.other	Wikipedia	en
dc.subject.other	Systems engineering	en
dc.title	Collective intelligence system engineering	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1643823.1643848	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1643823.1643848	en
heal.publicationDate	2009	en
heal.abstract	Collective intelligence (CI) is an emerging research field which aims at combining human and machine intelligence, to improve community processes usually performed by large groups. CI systems may be collaborative, like Wikipedia, or competitive, like a number of recently established problem-solving companies that attempt to find solutions to difficult R&D or marketing problems drawing on the competition among web users. The benefits that CI systems earn user communities, combined with the fact that they share a number of basic common characteristics, open up the prospect for the design of a general methodology that will allow the efficient development and evaluation of CI. In the present work, an attempt is made to establish the analytical foundations and main challenges for the design and construction of a generic collective intelligence system. First, collective intelligence systems are categorized into active and passive and specific examples of each category are provided. Then, the basic modeling framework of CI systems is described. This includes concepts such as the set of possible user actions, the CI system state and the individual and community objectives. Additional functions, which estimate the expected user actions, the future state of the system, as well as the level of objective fulfillment, are also established. In addition, certain key issues that need to be considered prior to system launch are also described. The proposed framework is expected to promote efficient CI design, so that the benefit gained by the community and the individuals through the use of CI systems, will be maximized. Copyright 2009 ACM.	en
heal.journalName	Proceedings of the International Conference on Management of Emergent Digital EcoSystems, MEDES '09	en
dc.identifier.doi	10.1145/1643823.1643848	en
dc.identifier.spage	134	en
dc.identifier.epage	140	en