Spatial groundings for meaningful symbols

The increasing availability of ontologies raises the need to establish relationships and make inferences across heterogeneous knowledge models. The approach proposed and supported by knowledge representation standards consists in establishing formal symbolic descriptions of a conceptualisation, which, it has been argued, lack grounding and are not expressive enough to allow to identify relations across separate ontologies. Ontology mapping approaches address this issue by exploiting structural or linguistic similarities between symbolic entities, which is costly, error-prone, and in most cases lack cognitive soundness. We argue that knowledge representation paradigms should have a better support for similarity and propose two distinct approaches to achieve it. We first present a representational approach which allows to ground symbolic ontologies by using Conceptual Spaces (CS), allowing for automated computation of similarities between instances across ontologies. An alternative approach is presented, which considers symbolic entities as contextual interpretations of processes in spacetime or Differences. By becoming a process of interpretation, symbols acquire the same status as other processes in the world and can be described (tagged) as well, which allows the bottom-up production of meaning

Rapprocher les ontologies et les folksonomies pour la gestion des connaissances partagées : un état de l'art.

International audienceCes dernières années, le “tagging social” s'est imposé au sein du Web 2.0 comme le principal moyen de classification de données en très grand nombre. Néanmoins, l'emploi pour la classification d'ensembles de tags non contrôlés, appelés folksonomies, pose plusieurs problèmes : le problème de l'ambiguïté (un tag dénotant plusieurs concepts), le problème de variations d'écritures (plusieurs tags dénotant un même concept) et le manque d'assistance à l'exploitation de ces structures (notamment pour la recherche ou l'échange d'informations) en l'absence de représentations explicites de ces connaissances partagées. Cet article présente un état de l'art comparatif et une discussion sur les travaux proposant une évolution de ces systèmes à base de folksonomies, en tenant compte, notamment, des travaux existant dans le domaine de la représentation des connaissances, en particulier ceux à base d'ontologies

Sémantique des folksonomies: structuration collaborative et assistée

National audienceThe advent of tagging and folksonomies for organizing shared ressources on the social Web brought promising opportunities to help communities of users capture their knowledge. However, the lack of semantics, or the spelling variations between tags lowers the potentials for browsing and exploring these data. To overcome these limitations, we propose exploiting the interactions between the users and the systems to validate or correct semantic analysis automatically applied to the tags. This process is based upon our model of the assistance of folksonomies enrichment which supports conflictual points of view. Several strategies can then be applied to propose novel browsing facilities to users

A Complete Life-Cycle for the Semantic Enrichment of Folksonomies

International audienceTags freely provided by users of social tagging services are not explicitly semantically linked, and this significantly hinders the possibilities for browsing and exploring these data. On the other hand, folksonomies provide great opportunities to bootstrap the construction of thesauri. We propose an approach to semantic enrichment of folksonomies that integrates both automatic processing and user input, while formally supporting multiple points of view. We take into account the social structure of our target communities to integrate the folksonomy enrichment process into everyday tasks. Our system allows individual users to navigate more efficiently within folksonomies, and also to maintain their own structure of tags while benefiting from others contributions. Our approach brings also solutions to the bottleneck problem of knowledge acquisition by helping communities to build thesauri by integrating the manifold contributions of all their members, thus providing for a truly socio-semantic solution to folksonomy enrichment and thesauri construction

Linking Folksonomies and Ontologies for Supporting Knowledge Sharing: a State of the Art

Deliverable of ISICIL ANR-funded projectSocial tagging systems have recently become very popular as a means to classify large sets of resources shared among on-line communities over the social Web. However, the folksonomies resulting from the use of these systems revealed limitations: tags are ambiguous and their spelling may vary, and folksonomies are difficult to exploit in order to retrieve or exchange information. This report compares the recent attempts to overcome these limitations and to support the use of folksonomies with formal languages and ontologies from the Semantic Web

Semantic Social Network Analysis: A Concrete Case

In this chapter we present our approach to analyzing such semantic social networks and capturing collective intelligence from collaborative interactions to challenge requirements of Enterprise 2.0. Our tools and models have been tested on an anonymized dataset from Ipernity.com, one of the biggest French social web sites centered on multimedia sharing. This dataset contains over 60,000 users, around half a million declared relationships of three types, and millions of interactions (messages, comments on resources, etc.). We show that the enriched semantic web framework is particularly well-suited for representing online social networks, for identifying their key features and for predicting their evolution. Organizing huge quantity of socially produced information is necessary for a future acceptance of social applications in corporate contexts