Probabilistic Logic
Compiling probabilistic logic programs into sentential decision diagrams
... We investigated the use of a new language, called Sentential Decision Diagrams, for compiling probabilistic logic programs. This language supports an efficient apply operator, not available for d-DNNFs, ...
10
Vulnerability analysis of cyber security modelling language models using probabilistic logic
... Computer systems are an essential asset of large companies such as banks, financial institutions, utility companies and telecommunication providers. Given their important roles for the functioning of society, these ...
112
Semantic Parsing using Distributional Semantics and Probabilistic Logic
... the probabilistic logic framework we use for the RTE task (we do not use PSL here as it shares the problems of fuzzy logic with proba- bilistic ...
5
The most probable explanation for probabilistic logic programs with annotated disjunctions
... a probabilistic logic and learning framework – a language and an ...on probabilistic facts, or binary random variables, the ProbLog language now also supports Annotated Disjunctions (ADs) ...of ...
15
Inference in Probabilistic Logic Programs Using Lifted Explanations
... In this paper, we consider the problem of lifted inference in the context of Prism-like probabilistic logic programming languages. Traditional inference in such languages involves the construction of an ...
15
Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces
... its probabilistic components in a common framework. Our probabilistic-logic bots (PL-bots) evaluate business rules by iteratively prompting users to provide the values of unknown ...of logic ...
6
On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics
... in probabilistic logic while taking into account the problems resulting from the domain closure assumption (DCA) and the closed-world assumption ...use probabilistic logic for natural language ...
11
Probabilistic Logic Programming with Beta-Distributed Random Variables
... several probabilistic variants of Prolog have been developed, such as ICL (Poole 2000), Dyna (Eisner, Goldlust, and Smith 2005), PRISM (Sato and Kameya 2001) and ProbLog (De Raedt, Kimmig, and Toivonen 2007), with ...
8
Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach
... Dependency parsing is a core task in NLP, and it is widely used by many applica- tions such as information extraction, ques- tion answering, and machine translation. In the era of social media, a big chal- lenge is that ...
7
Probabilistic abductive logic programming using Dirichlet priors
... abductive logic programs enriched with probabilistic ...in probabilistic logic programming, although both functional and logic program- ming are Turing complete, so they are equally ...
18
IPDL: A Probabilistic Dataflow Logic for Cryptography
... A probabilistic logic capturing reactions and dependencies IPDL encodes a distributed computation using channels and reactions : when all inputs to a reaction have been collected, the reaction is triggered ...
28
Probabilistic Soft Logic for Semantic Textual Similarity
... propriate probabilistic logic for STS than ...determining probabilistic logical ...Similarity Logic, based on its use of similar- ity ...Markov Logic with ...
10
Joint Prediction for Entity/Event Level Sentiment Analysis using Probabilistic Soft Logic Models
... Soft Logic. Probabilistic Soft Logic (PSL) is a variation of Markov Logic Net- works, which is a framework for probabilistic logic that employs weighted formulas in first- order ...
11
Link prediction using a probabilistic description logic
... first-order probabilistic logic [6]) are assumed; a single con- cept name appears in the left hand side of any inclusion or definition and in the conditioned side of any probabilistic inclusion; and ...
13
Probabilistic seismic hazard analysis using the logic tree approach – Patna district (India)
... The difference in a and b parameters is determined using the above methods, as it is calculated based on magnitude of completeness using mixed data (Woessner and Wiemer, 2005) instead of period of completeness for ...
19
Title: IMPLEMENTATION OF LOW POWER LOW NOISE PROBABILISTIC-BASED LOGIC DESIGNS
... at logic low, the latch is in latching mode and its output remains ...at logic high, the latch circuit enters into transparent mode, where its output logic state is determined by its input signal ...
5
Reasoning in non-probabilistic uncertainty: logic programming and neural-symbolic computing as examples
... I/O logic norms are represented as ordered pairs of formulas like (α, ...I/O logic is that it does not have (α, α) for any α ...I/O logic into an extended logic program to be processed by CILP ...
45
Asymmetry width probabilistic fuzzy logic system for rigid flexible manipulator modeling
... The probabilistic fuzzy set (PFS) and probabilistic fuzzy logic system is designed for handling the uncertainties with stochastic and nonstochastic ...asymmetric probabilistic fuzzy set is ...
6
Enabling Transitivity for Lexical Inference on Chinese Verbs Using Probabilistic Soft Logic
... select probabilistic soft logic (PSL) to model the lexical inference ...abilistic logic (Bach et ...their logic representations and ap- plying a PSL model to analyze word-to-word se- mantic ...
10
Probabilistic Couplings For Probabilistic Reasoning
... a probabilistic notion of ...generalized probabilistic bisimulation to probabilistic simulation; Jonsson and Larsen (1991, Definition ...theorem. Probabilistic (bi)simulation can be ...
147