In an electronic communication system, relevance levels of an incoming or outgoing message for presenting it to an interlocutor is measured without having to actually interact with the interlocutor, by a method comprising the steps of extracting from the message, a flow of digital signals pertaining to transmission/reception context features, to content of the message and/or to other interlocutors with the interlocutor; weighting probabilistically the digital signals by means of indicators of relative and interrelated frequencies of occurrences of the same digital signals extracted from previous messages; from the results of the above steps, auto-generating a Bayesian network that allows the interlocutor to obtain a probabilistic prediction on the attractiveness of sent/received signals or messages, or find most probably interested interlocutors for a given information or message, each node of the Bayesian network being associated with a signal.

 
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> Algorithmic testing in laboratory medicine

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