Probabilistic inference on uncertain semantic link network and its application in event identification

Volume: 104, Pages: 32 - 42
Published: Mar 1, 2020
Abstract
The Probabilistic Semantic Link Network (P-SLN) is a model for enhancing the ability of Semantic Link Network in representing uncertainty. Probabilistic inference over uncertain semantic links can process the likelihood and consistency of uncertain semantic links. This work develops the P-SLN model by incorporating probabilistic inference rules and consistency constraints. Two probabilistic inference mechanisms are incorporated into the model....
Paper Details
Title
Probabilistic inference on uncertain semantic link network and its application in event identification
Published Date
Mar 1, 2020
Volume
104
Pages
32 - 42
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