Abstract
Organizations and enterprises have developed complex data and information exchange systems that are now vital for their daily operations. Currently available systems, however, face a major challenge. On todays global information infrastructure, data semantics is more and more context- and time-dependent, and cannot be fixed once and for all at design time. Identifying emerging relationships among previously unrelated information items (e.g., during data interchange) may dramatically increase their business value. This chapter introduce and discuss the notion of Emergent Semantics (ES), where both the representation of semantics and the discovery of the proper interpretation of symbols are seen as the result of a selforganizing process performed by distributed agents, exchanging symbols and adaptively developing the proper interpretation via multi-party cooperation and conflict resolution. Emergent data semantics is dynamically dependent on the collective behaviour of large communities of agents, which may have different and even conflicting interests and agendas. This is a research paradigm interpreting semantics from a pragmatic prospective. The chapter introduce this notion providing a discussion on the principles, research area and current state of the art.
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Aiello, C., Catarci, T., Ceravolo, P., Damiani, E., Scannapieco, M., Viviani, M. (2008). Emergent Semantics in Distributed Knowledge Management. In: Nayak, R., Ichalkaranje, N., Jain, L.C. (eds) Evolution of the Web in Artificial Intelligence Environments. Studies in Computational Intelligence, vol 130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79140-9_9
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