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of 107
pro vyhledávání: '"Bellodi, Elena"'
The SARS-CoV-2 pandemic reminded us how vaccination can be a divisive topic on which the public conversation is permeated by misleading claims, and thoughts tend to polarize, especially on online social networks. In this work, motivated by recent nat
Externí odkaz:
http://arxiv.org/abs/2302.01028
Publikováno v:
Theory and Practice of Logic Programming, 21(5), 557-574, 2021
Uncertain information is being taken into account in an increasing number of application fields. In the meantime, abduction has been proved a powerful tool for handling hypothetical reasoning and incomplete knowledge. Probabilistic logical models are
Externí odkaz:
http://arxiv.org/abs/2108.03033
While there exist several reasoners for Description Logics, very few of them can cope with uncertainty. BUNDLE is an inference framework that can exploit several OWL (non-probabilistic) reasoners to perform inference over Probabilistic Description Lo
Externí odkaz:
http://arxiv.org/abs/2010.01087
Publikováno v:
Theory and Practice of Logic Programming 20 (2020) 641-655
In Probabilistic Logic Programming (PLP) the most commonly studied inference task is to compute the marginal probability of a query given a program. In this paper, we consider two other important tasks in the PLP setting: the Maximum-A-Posteriori (MA
Externí odkaz:
http://arxiv.org/abs/2008.01394
Publikováno v:
Theory and Practice of Logic Programming, 19 (3), 449-476, 2019
When modeling real world domains we have to deal with information that is incomplete or that comes from sources with different trust levels. This motivates the need for managing uncertainty in the Semantic Web. To this purpose, we introduced a probab
Externí odkaz:
http://arxiv.org/abs/1809.06180
Publikováno v:
In International Journal of Approximate Reasoning March 2022 142:41-63
Autor:
Bellodi, Elena1 (AUTHOR) elena.bellodi@unife.it
Publikováno v:
Intelligenza Artificiale. 2023, Vol. 17 Issue 1, p143-156. 14p.
Publikováno v:
Theory and Practice of Logic Programming 14 (2014) 681-695
Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances. Even if vari
Externí odkaz:
http://arxiv.org/abs/1405.3218
Autor:
Bellodi, Elena, Riguzzi, Fabrizio
Publikováno v:
Theory and Practice of Logic Programming 15 (2015) 169-212
Learning probabilistic logic programming languages is receiving an increasing attention and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both the structure and the parameters (SEM-CP-logic and SLIPCA
Externí odkaz:
http://arxiv.org/abs/1309.2080
Publikováno v:
In International Journal of Approximate Reasoning December 2017 91:216-232