FaD-CODS Fake News Detection on COVID-19 Using Description Logics and Semantic Reasoning

2021 ◽  
Vol 16 (3) ◽  
pp. 1-20
Author(s):  
Kartik Goel ◽  
Charu Gupta ◽  
Ria Rawal ◽  
Prateek Agrawal ◽  
Vishu Madaan
Keyword(s):  
Decision Making ◽  
Description Logic ◽  
State Of The Art ◽  
Description Logics ◽  
Formal Definition ◽  
Fake News ◽  
Web Based ◽  
Semantic Reasoning ◽  
Tool Performance ◽  
Disease Pattern

COVID-19 has affected people in nearly 180 countries worldwide. This paper presents a novel and improved Semantic Web-based approach for implementing the disease pattern of COVID-19. Semantics gives meaning to words and defines the purpose of words in a sentence. Previous ontology approaches revolved around syntactic methods. In this paper, semantics gives due priority to understand the nature and meaning of the underlying text. The proposed approach, FaD-CODS, focuses on a specific application of fake news detection. The formal definition is given by depiction of knowledge patterns using semantic reasoning. The proposed approach based on fake news detection uses description logic for semantic reasoning. FaD-CODS will affect decision making in medicine and healthcare. Further, the state-of-the-art method performs best for semantic text incorporated in the model. FaD-CODS used a reasoning tool, RACER, to check the consistency of the collected study. Further, the reasoning tool performance is critically analyzed to determine the conflicts between a myth and fact.

scholarly journals A Semantic Web-based Representation of Human-logical Inference for Solving Bongard Problems

2020 ◽  
Vol 26 (10) ◽  
pp. 1343-1363
Author(s):  
Jisha Maniamma ◽  
Hiroaki Wagatsuma
Keyword(s):  
Decision Making ◽  
Semantic Web ◽  
Description Logic ◽  
Logical Reasoning ◽  
Hierarchical Level ◽  
Logical Inference ◽  
Learning Abilities ◽  
Web Based ◽  
Wide Range ◽  
Target Frame

Bongard Problems (BPs) are a set of 100 visual puzzles introduced by M. M. Bongard in the mid-1960s. BPs have been established as benchmark puzzles for understanding the human context-based learning abilities to solve ill- posed problems. The puzzle requires the logical explanation as the answer to distinct two classes of figures from redundant options, which can be obtained by a thinking process to alternatively change the target frame (hierarchical level of analogy) of thinking from a wide range concept networks as D. R. Hofstadter suggested. Some minor research results to solve a limited set of BPs have reported based a single architecture accompanied with probabilistic approaches; however the central problem on BP's difficulties is the requirement of flexible changes of the target frame, therefore non-hierarchical cluster analyses does not provide the essential solution and hierarchical probabilistic models needs to include unnecessary levels for learning from the beginning to prevent a prompt decision making. We hypothesized that logical reasoning process with limited numbers of meta-data descriptions realizes the sophisticated and prompt decision-making and the performance is validated by using BPs. In this study, a semantic web-based hierarchical model to solve BPs was proposed as the minimum and transparent system to mimic human-logical inference process in solving of BPs by using the Description Logic (DL) with assertions on concepts (TBox) and individuals (ABox). Our results demonstrated that the proposed model not only provided individual solutions as a BP solver, but also proved the correctness of Hofstadter's idea as the flexible frame with concept networks for BPs in our actual implementation, which no one has ever achieved. This fact will open the new horizon for theories for designing of logical reasoning systems especially for critical judgments and serious decision-making as expert humans do in a transparent and descriptive way of why they judged in that manner.

scholarly journals Automated Reasoning in Modal and Description Logics via SAT Encoding: the Case Study of K(m)/ALC-Satisfiability

2009 ◽  
Vol 35 ◽  
pp. 343-389 ◽  
Author(s):  
R. Sebastiani ◽  
M. Vescovi
Keyword(s):  
Automated Reasoning ◽  
Description Logic ◽  
State Of The Art ◽  
Description Logics ◽  
Worst Case ◽  
Current State ◽  
Database Theory ◽  
Sat Encoding ◽  
Better Than

In the last two decades, modal and description logics have been applied to numerous areas of computer science, including knowledge representation, formal verification, database theory, distributed computing and, more recently, semantic web and ontologies. For this reason, the problem of automated reasoning in modal and description logics has been thoroughly investigated. In particular, many approaches have been proposed for efficiently handling the satisfiability of the core normal modal logic K(m), and of its notational variant, the description logic ALC. Although simple in structure, K(m)/ALC is computationally very hard to reason on, its satisfiability being PSPACE-complete. In this paper we start exploring the idea of performing automated reasoning tasks in modal and description logics by encoding them into SAT, so that to be handled by state-of-the-art SAT tools; as with most previous approaches, we begin our investigation from the satisfiability in K(m). We propose an efficient encoding, and we test it on an extensive set of benchmarks, comparing the approach with the main state-of-the-art tools available. Although the encoding is necessarily worst-case exponential, from our experiments we notice that, in practice, this approach can handle most or all the problems which are at the reach of the other approaches, with performances which are comparable with, or even better than, those of the current state-of-the-art tools.

scholarly journals Hypertableau Reasoning for Description Logics

2009 ◽  
Vol 36 ◽  
pp. 165-228 ◽  
Author(s):  
B. Motik ◽  
R. Shearer ◽  
I. Horrocks
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Description Logic ◽  
State Of The Art ◽  
Description Logics ◽  
Primary Sources ◽  
Performance Improvements ◽  
Introduction Rule ◽  
Significant Performance ◽  
Representation Formalism

We present a novel reasoning calculus for the description logic SHOIQ^+---a knowledge representation formalism with applications in areas such as the Semantic Web. Unnecessary nondeterminism and the construction of large models are two primary sources of inefficiency in the tableau-based reasoning calculi used in state-of-the-art reasoners. In order to reduce nondeterminism, we base our calculus on hypertableau and hyperresolution calculi, which we extend with a blocking condition to ensure termination. In order to reduce the size of the constructed models, we introduce anywhere pairwise blocking. We also present an improved nominal introduction rule that ensures termination in the presence of nominals, inverse roles, and number restrictions---a combination of DL constructs that has proven notoriously difficult to handle. Our implementation shows significant performance improvements over state-of-the-art reasoners on several well-known ontologies.

scholarly journals Development of an electronic conversation aid to support shared decision making for children with acute otitis media

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jana L Anderson ◽  
e Silva Lucas Oliveira J ◽  
Juan P Brito ◽  
Ian G Hargraves ◽  
Erik P Hess
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Otitis Media ◽  
Acute Otitis Media ◽  
Medical Knowledge ◽  
Complication Rates ◽  
Shared Decision ◽  
Web Based ◽  
Quality Issue ◽  
The Impact

Abstract Objective The overuse of antibiotics for acute otitis media (AOM) in children is a healthcare quality issue in part arising from conflicting parent and physician understanding of the risks and benefits of antibiotics for AOM. Our objective was to develop a conversation aid that supports shared decision making (SDM) with parents of children who are diagnosed with non-severe AOM in the acute care setting. Materials and Methods We developed a web-based encounter tool following a human-centered design approach that includes active collaboration with parents, clinicians, and designers using literature review, observations of clinical encounters, parental and clinician surveys, and interviews. Insights from these processes informed the iterative creation of prototypes that were reviewed and field-tested in patient encounters. Results The ear pain conversation aid includes five sections: (1) A home page that opens the discussion on the etiologies of AOM; (2) the various options available for AOM management; (3) a pictograph of the impact of antibiotic therapy on pain control; (4) a pictograph of complication rates with and without antibiotics; and (5) a summary page on management choices. This open-access, web-based tool is located at www.earpaindecisionaid.org. Conclusions We collaboratively developed an evidence-based conversation aid to facilitate SDM for AOM. This decision aid has the potential to improve parental medical knowledge of AOM, physician/parent communication, and possibly decrease the overuse of antibiotics for this condition.

A Set-theoretic Approach to Reasoning Services for the Description Logic 𝒟 ℒ D 4,×

2020 ◽  
Vol 176 (3-4) ◽  
pp. 349-384
Author(s):  
Domenico Cantone ◽  
Marianna Nicolosi-Asmundo ◽  
Daniele Francesco Santamaria
Keyword(s):  
Description Logic ◽  
Description Logics ◽  
Theoretic Approach ◽  
The Novel ◽  
Data Types ◽  
Left Hand ◽  
Rule Languages ◽  
Tableau System ◽  
High Scalability ◽  
Better Than

In this paper we consider the most common TBox and ABox reasoning services for the description logic 𝒟ℒ〈4LQSR,x〉(D) ( 𝒟 ℒ D 4,× , for short) and prove their decidability via a reduction to the satisfiability problem for the set-theoretic fragment 4LQSR. 𝒟 ℒ D 4,× is a very expressive description logic. It combines the high scalability and efficiency of rule languages such as the SemanticWeb Rule Language (SWRL) with the expressivity of description logics. In fact, among other features, it supports Boolean operations on concepts and roles, role constructs such as the product of concepts and role chains on the left-hand side of inclusion axioms, role properties such as transitivity, symmetry, reflexivity, and irreflexivity, and data types. We further provide a KE-tableau-based procedure that allows one to reason on the main TBox and ABox reasoning tasks for the description logic 𝒟 ℒ D 4,× . Our algorithm is based on a variant of the KE-tableau system for sets of universally quantified clauses, where the KE-elimination rule is generalized in such a way as to incorporate the γ-rule. The novel system, called KEγ-tableau, turns out to be an improvement of the system introduced in [1] and of standard first-order KE-tableaux [2]. Suitable benchmark test sets executed on C++ implementations of the three mentioned systems show that in several cases the performances of the KEγ-tableau-based reasoner are up to about 400% better than the ones of the other two systems.

scholarly journals State-of-the-Art Prescriptive Criteria Weight Elicitation

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Mona Riabacke ◽  
Mats Danielson ◽  
Love Ekenberg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Theory ◽  
Decision Analysis ◽  
Analytical Methods ◽  
State Of The Art ◽  
Criteria Weights ◽  
Decision Making Processes ◽  
Method Of Assessment ◽  
Descriptive Theories

Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

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