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Information retrieval is not only the most frequent application executed onthe Web but it is also the base of different types of applications. Consideringcollective intelligence of groups of individuals as a framework for evaluatingand incorporating new experiences and information we often cannot retrieve suchknowledge being tacit. Tacit knowledge underlies many competitive capabilitiesand it is hard to articulate on discrete ontology structure. It is unstructuredor unorganized, and therefore remains hidden. Developing generic solutions thatcan find the hidden knowledge is extremely complex. Moreover this will be agreat challenge for the developers of semantic technologies. This work aims toexplore ways to make explicit and available the tacit knowledge hidden in thecollective intelligence of a collaborative environment within organizations.The environment was defined by folksonomies supported by a faceted semanticsearch. Vector space model which incorporates an analogy with the mathematicalapparatus of quantum theory is adopted for the representation and manipulationof the meaning of folksonomy. Vector space retrieval has been proven efficiencywhen there isn't a data behavioural because it bears ranking algorithmsinvolving a small number of types of elements and few operations. A solution tofind what the user has in mind when posing a query could be based on "jointmeaning" understood as a joint construal of the creator of the contents and thereader of the contents. The joint meaning was proposed to deal with vaguenesson ontology of folksonomy indeterminacy, incompleteness and inconsistencies oncollective intelligence. A proof-of concept prototype was built forcollaborative environment as evolution of the actual social networks (likeFacebook, LinkedIn,..) using the information visualization on a RIA applicationwith Semantic Web techniques and technologies.

Search for Hidden Knowledge in Collective Intelligence dealing Indeterminacy Ontology of Folksonomy with Linguistic Pragmatics and Quantum Logic