Language Evolution and Computation Bibliography

In this paper, we investigate the combination of collaborative tagging and emergent semantics for improved data navigation and search. We propose to use visual features in addition to tags provided by users in order to discover new relationships between data. We show that our method is able to overcome some of the problems involved in navigating databases using tags only, such as synonymy or different languages, spelling mistakes, homonymy, or missing tags. On the other hand, image search based on visual features can be simplified substantially by the use of tags. We present technical details of our prototype system and show some preliminary results.

We study the exchange of information in collective informa- tion systems mediated by information agents, focusing specifically on the problem of semantic interoperability. We advocate the use of mecha- nisms inspired from natural language, that enable each agent to develop a repertoire of grounded categories and labels for these categories and negotiate their use with other agents. The communication system as well as its semantics is hence emergent and adaptive instead of predefined. It is the result of a self-organised semiotic dynamics where relations be- tween data, labels for the data, and the categories associated with the labels undergo constant evolution.