CorpWiki: A self-regulating wiki to promote corporate collective intelligence through expert peer matching

Lykourentzou, I; Papadaki, K; Vergados, DJ; Polemi, D; Loumos, V

dc.contributor.author	Lykourentzou, I	en
dc.contributor.author	Papadaki, K	en
dc.contributor.author	Vergados, DJ	en
dc.contributor.author	Polemi, D	en
dc.contributor.author	Loumos, V	en
dc.date.accessioned	2014-03-01T01:33:04Z
dc.date.available	2014-03-01T01:33:04Z
dc.date.issued	2010	en
dc.identifier.issn	0020-0255	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20305
dc.subject	Collective intelligence	en
dc.subject	Expert peer matching	en
dc.subject	Feed-forward neural networks	en
dc.subject	Web 2.0	en
dc.subject	Wiki	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.other	Collective intelligence	en
dc.subject.other	Collective intelligences	en
dc.subject.other	Corporate environment	en
dc.subject.other	Corporate knowledge	en
dc.subject.other	Expert peer matching	en
dc.subject.other	High quality	en
dc.subject.other	Human networks	en
dc.subject.other	Knowledge creations	en
dc.subject.other	Machine-learning	en
dc.subject.other	Organizational intelligence	en
dc.subject.other	Peer matching	en
dc.subject.other	Performance evaluation	en
dc.subject.other	Quality assessment	en
dc.subject.other	Quality levels	en
dc.subject.other	Simulation modeling	en
dc.subject.other	Web 2.0	en
dc.subject.other	Wiki	en
dc.subject.other	Computer simulation	en
dc.subject.other	Neural networks	en
dc.subject.other	Personnel	en
dc.subject.other	World Wide Web	en
dc.subject.other	Quality control	en
dc.title	CorpWiki: A self-regulating wiki to promote corporate collective intelligence through expert peer matching	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ins.2009.08.003	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ins.2009.08.003	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	One of the main challenges that organizations face nowadays, is the efficient use of individual employee intelligence, through machine-facilitated understanding of the collected corporate knowledge, to develop their collective intelligence. Web 2.0 technologies, like wikis, can be used to address the above issue. Nevertheless, their application in corporate environments is limited, mainly due to their inability to ensure knowledge creation and assessment in a timely and reliable manner. In this study we propose CorpWiki, a self-regulating wiki system for effective acquisition of high-quality knowledge content. Inserted articles undergo a quality assessment control by a large number of corporate peer employees. In case the quality is inadequate, CorpWiki uses a novel expert peer matching algorithm (EPM), based on feed-forward neural networks, that searches the human network of the organization to select the most appropriate peer employee who will improve the quality of the article. Performance evaluation results, obtained through simulation modeling, indicate that CorpWiki improves the final quality levels of the inserted articles as well as the time and effort required to reach them. The proposed system, combining machine-learning intelligence with the individual intelligence of peer employees, aims to create new inferences regarding corporate issues, thus promoting the collective organizational intelligence. (C) 2009 Elsevier Inc. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Information Sciences	en
dc.identifier.doi	10.1016/j.ins.2009.08.003	en
dc.identifier.isi	ISI:000272108200003	en
dc.identifier.volume	180	en
dc.identifier.issue	1	en
dc.identifier.spage	18	en
dc.identifier.epage	38	en