Article
Computer Science, Information Systems
Messaouda Fareh, Ishak Riali, Hafsa Kherbache, Marwa Guemmouz
Summary: The World Health Organization (WHO) has declared the novel Coronavirus a pandemic. Predicting the diagnosis of COVID-19 is crucial for disease control and treatment. This paper proposes an approach that utilizes probabilistic ontologies to address the uncertainty and incompleteness of knowledge, aiming to predict the COVID-19 diagnosis. By constructing the entities, attributes, and relationships of COVID-19 ontology, probabilistic components are developed using a Multi-Entity Bayesian Network. The results show promising potential for fast medical assistance.
COMPUTER SCIENCE AND INFORMATION SYSTEMS
(2023)
Article
Neurosciences
Lupita Estefania Gazzo Castaneda, Benjamin Sklarek, Dennis E. Dal Mas, Markus Knauff
Summary: Reasoning is the process of inferring new conclusions from given premises. Deductive reasoning preserves truth and conclusions are either true or false. Probabilistic reasoning is based on degrees of belief and conclusions can be more or less likely. However, some researchers have argued that what appears to be deductive reasoning may actually be probabilistic inference with extreme probabilities. An fMRI experiment was conducted to test this assumption, and the results showed that deductive and probabilistic reasoning rely on different neurocognitive processes, people can suppress prior knowledge to reason deductively, and not all inferences can be reduced to probabilistic reasoning.
Article
Computer Science, Artificial Intelligence
Nicolas Ferranti, Stenio Sa Rosario Furtado Soares, Jairo Francisco de Souza
Summary: Ontologies establish meanings for information, solving data semantic heterogeneity issues and aiding information exchange, but using multiple ontologies may introduce ambiguity. Ontology matching searches for relationships between entities of distinct ontologies, addressing semantic heterogeneity problems in data, and has seen various metaheuristics-based meta-matching approaches proposed to tackle this issue.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Software Engineering
Luigi Bellomarini, Eleonora Laurenza, Emanuel Sallinger, Evgeny Sherkhonov
Summary: This paper presents a framework for probabilistic reasoning in Vadalog-based Knowledge Graphs. It introduces Soft Vadalog as a probabilistic extension to Vadalog, allowing for handling uncertainty in knowledge graphs. The paper discusses the theory and presents a practical Monte Carlo method, MCMC-chase, for using Soft Vadalog.
THEORY AND PRACTICE OF LOGIC PROGRAMMING
(2022)
Article
Computer Science, Artificial Intelligence
Abdelweheb Gueddes, Mohamed Ali Mahjoub
Summary: The proposed paper aims to develop a remote intervention assistance system for individuals in difficulty, which is crucial due to the aging population. The system utilizes an ontological approach along with Semantic Web Rule Language (SWRL) and Probabilistic Web Ontology Language (PR-OWL) to enable machine analysis and decision-making. The paper also proposes two additional approaches using Jena Application Programming Interfaces (API) and tests them in a simulation. Feedback from users demonstrates the effectiveness of the system and its potential for future research and development in this field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
Summary: DeepProbLog is a neural probabilistic logic programming language that supports symbolic and subsymbolic representations and inference, program induction, probabilistic programming, and learning from examples. It integrates general-purpose neural networks and expressive probabilistic-logical modeling and reasoning, allowing end-to-end training based on examples.
ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Xingsi Xue, Chao Jiang, Jie Zhang, Hai Zhu, Chaofan Yang
Summary: The paper introduces a Siamese Neural Network based Ontology Matching technique for aligning sensor ontologies, which efficiently determines high-quality sensor ontology alignments. By using representative concepts extraction method and alignment refining method, the technique enhances model performance and alignment quality.
PEERJ COMPUTER SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Nicolas Ferranti, Jairo Francisco de Souza, Stenio Sa Rosario Furtado Soares
Summary: New ontology matching approaches are published every year to address the heterogeneity problem. Combining different alignment techniques can improve accuracy by capturing more entity characteristics. Local search-based meta-heuristics show good performance and accuracy compared to global optimization meta-heuristics.
KNOWLEDGE AND INFORMATION SYSTEMS
(2021)
Article
Computer Science, Information Systems
Bingquan Chen, Jinde Cao, Jie Zhong, Lianglin Xiong
Summary: This paper investigates the asymptotic set stability of probabilistic logical networks with random impulsive disturbances, proposing novel methods to reduce complexity. An HMC is obtained by sampling at impulsive instants, leading to necessary conditions for stability of the impulsive network.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Yael Konforti, Alon Shpigler, Boaz Lerner, Aharon Bar-Hillel
Summary: Convolutional neural networks (CNNs) have achieved high accuracy in visual-related tasks, but interpreting their intermediate layers and understanding their decision-making process is challenging. The SIGN method introduces probabilistic models to model the hidden layer activity in CNNs. The models estimate transition probabilities between clusters in consecutive layers and identify paths of inference. These inference graphs help understand the overall inference process and explain the network's decisions about specific images.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Remote Sensing
Bilge Kaan Karamete, Louai Adhami, Eli Glaser
Summary: A study has developed an adaptive scheme to modify the Markov Chain kernel window in order to reduce mistakes caused by narrower MC widths as GPS samples are collected. By temporarily increasing the MC window width based on geodesic distances, the results have significantly improved with manageable increase in computational cost. The algorithm's effectiveness is validated through example routes extracted from various vehicle trips.
GEO-SPATIAL INFORMATION SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Jie Zhong, Zongxi Yu, Yuanyuan Li, Jianquan Lu
Summary: This article studies state estimation for probabilistic Boolean networks through observing output sequences. The concept of detectability measure is proposed to quantitatively assess state estimation, and a stochastic state estimator is designed based on nondeterministic stochastic finite automaton. This approach further performs quantitative analysis on detectability through defining a Markov chain.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Qiu Ji, Weizhuo Li, Shiqi Zhou, Guilin Qi, Yuanfang Li
Summary: Ontologies, as the core building blocks of the Semantic Web, provide shared vocabularies and conceptual knowledge for specific application fields. However, logical conflicts often arise in actual application scenarios due to disjointness or negation in the ontologies. Incoherence and inconsistency are two types of logical conflicts. Handling incoherence is important as it can lead to inconsistency and affect the correctness of semantic reasoning. Various incoherent ontologies are essential for evaluating methods to handle incoherence.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Plant Sciences
Xingsi Xue, Pei-Wei Tsai
Summary: This study proposes an Adaptive Compact Evolutionary Algorithm (ACEA) to address the problem of aligning ecology and biodiversity ontologies. By utilizing semantic reasoning and optimization techniques, the algorithm improves performance and achieves better results compared to other aligning techniques in experiments.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Computer Science, Information Systems
Houda Akremi, Sami Zghal
Summary: This research introduces a new generic approach of fuzzification that allows semantic representation of crisp and fuzzy data in a domain ontology. The experimental results demonstrate that this approach outperforms the crisp one in terms of completeness, comprehensiveness, generality, comprehension, and shareability.
FRONTIERS OF COMPUTER SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Zahy Bnaya, Ariel Felner, Dror Fried, Olga Maksin, Solomon Eyal Shimony
Article
Computer Science, Artificial Intelligence
Shahaf S. Shperberg, Solomon Eyal Shimony
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
(2017)
Article
Computer Science, Artificial Intelligence
Erez Karpas, Oded Betzalel, Solomon Eyal Shimony, David Tolpin, Ariel Felner
ARTIFICIAL INTELLIGENCE
(2018)
Article
Computer Science, Artificial Intelligence
Erez Karpas, Solomon Eyal Shimony, Amos Beimel
ARTIFICIAL INTELLIGENCE
(2009)
Article
Mathematics, Applied
D. Berend, R. Brafman, S. Cohen, S. E. Shimony, S. Zucker
DISCRETE APPLIED MATHEMATICS
(2014)
Article
Automation & Control Systems
David Tolpin, Solomon Eyal Shimony
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
(2012)
Article
Computer Science, Artificial Intelligence
Maxim Binshtok, Ronen I. Brafman, Carmel Domshlak, Solomon E. Shimony
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
(2009)
Article
Computer Science, Theory & Methods
Dror Fried, Solomon Eyal Shimony, Amit Benbassat, Cenny Wenner
THEORETICAL COMPUTER SCIENCE
(2013)
Article
Mathematics, Applied
Daniel Berend, Ronen Brafman, Solomon E. Shimony, Shira Zucker, Shimon Cohen
DISCRETE APPLIED MATHEMATICS
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Daniel Berend, Shimon Cohen, Solomon E. Shimony, Shira Zucker
MODELLING, COMPUTATION AND OPTIMIZATION IN INFORMATION SYSTEMS AND MANAGEMENT SCIENCES - MCO 2015, PT 1
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Liat Cohen, Solomon Eyal Shimony, Gera Weiss
PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI)
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
David Tolpin, Oded Betzalel, Ariel Felner, Solomon Eyal Shimony
21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014)
(2014)
Proceedings Paper
Computer Science, Artificial Intelligence
Zahy Bnaya, Ariel Felner, Solomon Eyal Shimony
21ST INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-09), PROCEEDINGS
(2009)
Article
Computer Science, Artificial Intelligence
David Tolpin, Solomon Eyal Shimony
INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS
(2012)
Article
Computer Science, Hardware & Architecture
Flavia Bonomo-Braberman, Nick Brettell, Andrea Munaro, Daniel Paulusma
Summary: This article discusses the convexity and mim-width of bipartite graphs, and it proves that for certain families of graphs 7-t, the 7-t-convex graphs can be solved in polynomial time for NP-complete problems. It also explores the bounded and unbounded mim-width of 7-t-convex graphs for different sets 7-t.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Keqin Li
Summary: In this paper, we propose a computation offloading strategy to satisfy all UEs served by an MEC and develop an efficient method to find such a strategy. By using Markov chains to characterize UE mobility and calculating the joint probability distribution of UE locations, we can obtain the average response time of UEs and predict the overall average response time of tasks. Additionally, we solve the power constrained MEC speed setting problem.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Correction
Computer Science, Hardware & Architecture
Peter L. Bartlett, Philip M. Long
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Philipp Czerner, Roland Guttenberg, Martin Helfrich, Javier Esparza
Summary: This paper presents a construction method that produces population protocols with a small number of states, while achieving near-optimal expected number of interactions, for deciding Presburger predicates.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Katharina T. Huber, Leo van Iersel, Remie Janssen, Mark Jones, Vincent Moulton, Yukihiro Murakami, Charles Semple
Summary: This paper investigates the relationship between undirected and directed phylogenetic networks, and provides corresponding algorithms. The study reveals that the directed phylogenetic network is unique under specific conditions. Additionally, an algorithm for directing undirected binary networks is described, applicable to certain classes of directed phylogenetic networks.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Francesco Betti Sorbelli, Alfredo Navarra, Lorenzo Palazzetti, Cristina M. Pinotti, Giuseppe Prencipe
Summary: This study discusses the deployment of IoT sensors in an area that needs to be monitored. Drones are used to collect data from the sensors, but they have energy and storage constraints. To maximize the overall reward from the collected data and ensure compliance with energy and storage limits, an optimization problem called Multiple-drone Data-collection Maximization Problem (MDMP) is proposed and solved using an Integer Linear Programming algorithm.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Carla Binucci, Emilio Di Giacomo, William J. Lenhart, Giuseppe Liotta, Fabrizio Montecchiani, Martin Nollenburg, Antonios Symvonis
Summary: In this study, we investigate the problem of representing a graph as a storyplan, which is a model for dynamic graph visualization. We prove the NP-completeness of this problem and propose two parameterized algorithms as solutions. We also demonstrate that partial 3-trees always admit a storyplan and can be computed in linear time. Additionally, we show that even if the vertex appearance order is given, the problem of choosing how to draw the frames remains NP-complete.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Leszek Gasieniec, Tomasz Jurdzinski, Ralf Klasing, Christos Levcopoulos, Andrzej Lingas, Jie Min, Tomasz Radzik
Summary: This passage describes the Bamboo Garden Trimming Problem and presents approximation algorithms for both Discrete BGT and Continuous BGT.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)