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Change comment: Migrated property [contesto] from class [Talks.TalkClass]

Summary

Details

Talks.TalkClass[0]
Abstract
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1 +Nowadays, news management systems present new critical challenges in the knowledge management process: the ever-increasing amount of information to handle, its hetero- geneity in structure, and the pace at which it is made available are just a few to mention. Features such as autonomy and self- organisation are apparently essential to face challenges of such a sort: we foresee systems where news are generated in shared spaces – compartments – as molecules of knowledge, which self- aggregate and autonomously move toward news prosumers— e.g., journalists. Along this line, we discuss the Molecules of Knowledge (MoK) model for self-organising news management, featuring biochemical tuple spaces for creation, aggregation, diffusion and consumption of news. We discuss the MoK general computational model and describe its main abstractions, then we focus on news management, showing how to integrate the state-of-art international standards for news representation and dissemination in MoK, thus leading to the MoK-News domain-specific model; finally we discuss our first experiments in self-organising knowledge-oriented coordination for news management.
Authors
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1 +XWiki.AndreaOmicini,XWiki.SMariani
Category
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1 +Talk
Context
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1 +ASENSIS @ SASO 2012
Date
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1 +2012-09-10 00:00:00.0
APICe Event
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1 +Events.Asensis2012
Language
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1 +en
Note
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1 +#includeMacros("Publications.MacroSheet")
2 +This talk discusses the paper &ldquo;#pubTitleLink("MokAsensis2012")&rdquo;, presented at the 1st International Workshop on Adaptive Service Ecosystems: Natural and Socially Inspired Solutions ([ASENSIS 2012|http://apice.unibo.it/xwiki/bin/view/ASENSIS/]).
Place
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1 +Lyon, France
Slides
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1 +MO-ASENSIS2012.pdf
SlideShare
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1 +http://www.slideshare.net/andreaomicini/selforganising-news-management-the-molecules-of-knowledge-approach
Sources
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1 +MO-ASENSIS2012.zip
Speakers
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1 +XWiki.SMariani
Title
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1 +Self-Organising News Management: The Molecules of Knowledge Approach
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