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Typus
Verschleierung
Bearbeiter
Hindemith
Gesichtet
Yes.png
Untersuchte Arbeit:
Seite: 88, Zeilen: 21-33
Quelle: Dombroski Carley 2002
Seite(n): 1, Zeilen: 14-24
NETEST – It is based on the combination of multi-agent technology with hierarchical Bayesian inference models and biased net models to produce accurate posterior network representations. Bayesian inference models produce representations of a network’s structure and informant accuracy by combining prior network and accuracy data with informant perceptions of a network. Biased net theory examines and captures the biases that may be present within a specific network or group of networks. NETEST provides functionalities to estimate a network’s size, determine its membership and structure, determine areas of the network where data is missing, perform cost and benefit analysis of additional information, assess group level capabilities [embedded in the network, and pose “what if” scenarios to destabilize a network and predict its evolution over time.] NETEST is a tool that combines multiagent technology with hierarchical Bayesian inference models and biased net models to produce accurate posterior representations of a network. Bayesian inference models produce representations of a network’s structure and informant accuracy by combining prior network and accuracy data with informant perceptions of a network. Biased net theory examines and captures the biases that may exist in a specific network or set of networks. Using NETEST, an investigator has the power to estimate a network’s size, determine its membership and structure, determine areas of the network where data is missing, perform cost/benefit analysis of additional information, assess group level capabilities embedded in the network, and pose “what if” scenarios to destabilize a network and predict its evolution over time.
Anmerkungen

The source is given in the bibliography, but nowhere close to this text fragment.

Sichter
(Hindemith), WiseWoman

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