2 research outputs found
Emergent Behaviors from Folksonomy Driven Interactions
To reflect the evolving knowledge on the Web this paper considers ontologies
based on folksonomies according to a new concept structure called
"Folksodriven" to represent folksonomies. This paper describes a research
program for studying Folksodriven tags interactions leading to Folksodriven
cluster behavior. The goal of the research is to understand the type of simple
local interactions which produce complex and purposive group behaviors on
Folksodriven tags. We describe a synthetic, bottom-up approach to studying
group behavior, consisting of designing and testing a variety of social
interactions and cultural scenarios with Folksodriven tags. We propose a set of
basic interactions which can be used to structure and simplify the process of
both designing and analyzing emergent group behaviors. The presented behavior
repertories was developed and tested on a folksonomy environment.Comment: 6 pages, 5 figures; for details see: http://www.maxdalmas.com arXiv
admin note: text overlap with arXiv:1612.0957
Search for Hidden Knowledge in Collective Intelligence dealing Indeterminacy Ontology of Folksonomy with Linguistic Pragmatics and Quantum Logic
Information retrieval is not only the most frequent application executed on
the Web but it is also the base of different types of applications. Considering
collective intelligence of groups of individuals as a framework for evaluating
and incorporating new experiences and information we often cannot retrieve such
knowledge being tacit. Tacit knowledge underlies many competitive capabilities
and it is hard to articulate on discrete ontology structure. It is unstructured
or unorganized, and therefore remains hidden. Developing generic solutions that
can find the hidden knowledge is extremely complex. Moreover this will be a
great challenge for the developers of semantic technologies. This work aims to
explore ways to make explicit and available the tacit knowledge hidden in the
collective intelligence of a collaborative environment within organizations.
The environment was defined by folksonomies supported by a faceted semantic
search. Vector space model which incorporates an analogy with the mathematical
apparatus of quantum theory is adopted for the representation and manipulation
of the meaning of folksonomy. Vector space retrieval has been proven efficiency
when there isn't a data behavioural because it bears ranking algorithms
involving a small number of types of elements and few operations. A solution to
find what the user has in mind when posing a query could be based on "joint
meaning" understood as a joint construal of the creator of the contents and the
reader of the contents. The joint meaning was proposed to deal with vagueness
on ontology of folksonomy indeterminacy, incompleteness and inconsistencies on
collective intelligence. A proof-of concept prototype was built for
collaborative environment as evolution of the actual social networks (like
Facebook, LinkedIn,..) using the information visualization on a RIA application
with Semantic Web techniques and technologies.Comment: 17 pages, 7 figures, 2 tables; for details see:
http://www.maxdalmas.co