scholarly journals Reasoning in the presence of inconsistency through Preferential ALC

10.29007/8qr4 ◽  
2018 ◽  
Author(s):  
Graham Deane ◽  
Krysia Broda ◽  
Alessandra Russo
Keyword(s):  
Knowledge Base ◽  
Description Logic ◽  
Total Weight ◽  
Tableau Algorithm ◽  
Modified Algorithm ◽  
Answer Set

This paper presents an inconsistency tolerant semantics for the Description Logic ALC called Preferential ALC (p-ALC). A p-ALC knowledge base is comprised of defeasible and non-defeasible axioms. The defeasible ABox and TBox are labelled with confidence weights that could reflect an axiom's provenance. Entailment is defined through the notion of preferred interpretations which minimise the total weight of the inconsistent axioms. We introduce a modified ALC tableau algorithm in which the open branches give rise to the preferred interpretations, and show that it can compute p-ALC entailment by refutation. The modified algorithm is implemented as an incremental answer set program (ASP) that exploits optimisation to capture preferred interpretations of p-ALC.

scholarly journals Knowledge Representation of Highly Dynamic Ontologies Using Defeasible Logic

2021 ◽  
Vol 10 (2) ◽  
pp. 948-954
Keyword(s):  
Computational Complexity ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Description Logic ◽  
Defeasible Logic ◽  
Small Domain ◽  
Automated Support ◽  
Logical Rules

Description logic gives us the ability of reasoning with acceptable computational complexity with retaining the power of expressiveness. The power of description logic can be accompanied by the defeasible logic to manage non-monotonic reasoning. In some domains, we need flexible reasoning and knowledge representation to deal the dynamicity of such domains. In this paper, we present a DL representation for a small domain that describes the connections between different entities in a university publication system to show how could we deal with changeability in domain rules. An automated support can be provided on the basis of defeasible logical rules to represent the typicality in the knowledge base and to solve the conflicts that might happen.

The Fuzzy Description Logic ALCFH with Hedge Algebras as Concept Modifiers

2003 ◽  
Vol 7 (3) ◽  
pp. 294-305 ◽  
Author(s):  
Steffen Hölldobler ◽  
◽  
Hans-Peter Störr ◽  
Tran Dinh Khang ◽  
Keyword(s):  
Knowledge Base ◽  
Decision Procedure ◽  
Description Logic ◽  
Ordered Set ◽  
Fuzzy Description ◽  
Linearly Ordered Set

In this paper we present the fuzzy description logic ALCFH introduced, where primitive concepts are modified by means of hedges taken from hedge algebras. ALCFH is strictly more expressive than Fuzzy-ALC defined in [11]. We show that given a linearly ordered set of hedges primitive concepts can be modified to any desired degree by prefixing them with appropriate chains of hedges. Furthermore, we define a decision procedure for the unsatisfiability problem in ALCFH, and discuss knowledge base expansion when using terminologies, truth bounds, expressivity as well as complexity issues. We extend [8] by allowing modifiers on non-primitive concepts and extending the satisfiability procedure to handle concept definitions.

A Dual Description Logic for the Relations in Databases

2011 ◽  
Vol 474-476 ◽  
pp. 168-171
Author(s):  
Feng Zhi Li
Keyword(s):  
Knowledge Base ◽  
Description Logic ◽  
Logical Language ◽  
The Difference ◽  
Attribute Value

This paper introduced a dual description logic for relations, in order to represent the difference of tuples and attribute values. In the logic, concepts are classified into two classes as follows: tuple-concepts and attribute-value concepts. This paper firstly gives the logical language, syntax and semantics of the logic, and secondly defines a transformation of a relation in a database into a knowledge base in the dual description logic, and last proposes a transformation of a model for the dual description logic into a relation.

scholarly journals Forgetting in Answer Set Programming – A Survey

2021 ◽  
pp. 1-43
Author(s):  
RICARDO GONÇALVES ◽  
MATTHIAS KNORR ◽  
JOÃO LEITE
Keyword(s):  
Computational Complexity ◽  
Knowledge Base ◽  
Answer Set Programming ◽  
Complete Picture ◽  
Variable Elimination ◽  
Application Requirements ◽  
Answer Set

Abstract Forgetting – or variable elimination – is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant. In recent years, many different approaches for forgetting in Answer Set Programming have been proposed, in the form of specific operators, or classes of such operators, commonly following different principles and obeying different properties. Each such approach was developed to address some particular view on forgetting, aimed at obeying a specific set of properties deemed desirable in such view, but a comprehensive and uniform overview of all the existing operators and properties is missing. In this article, we thoroughly examine existing properties and (classes of) operators for forgetting in Answer Set Programming, drawing a complete picture of the landscape of these classes of forgetting operators, which includes many novel results on relations between properties and operators, including considerations on concrete operators to compute results of forgetting and computational complexity. Our goal is to provide guidance to help users in choosing the operator most adequate for their application requirements.

scholarly journals Translating OWL and semantic web rules into prolog: Moving toward description logic programs

2008 ◽  
Vol 8 (3) ◽  
pp. 301-322 ◽  
Author(s):  
KEN SAMUEL ◽  
LEO OBRST ◽  
SUZETTE STOUTENBERG ◽  
KAREN FOX ◽  
PAUL FRANKLIN ◽  
...  
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Automated Reasoning ◽  
Description Logic ◽  
Logic Programs ◽  
Dynamic Changes ◽  
General Rules ◽  
Alternative Approaches ◽  
Run Time

AbstractWe are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient automated reasoning on ontologies and rules, by translating all of them into Prolog and adding a set of general rules that properly capture the semantics of OWL. We have also enabled the user to make dynamic changes on the fly, at run time. This work addresses several of the concerns expressed in previous work, such as negation, complementary classes, disjunctive heads, and cardinality, and it discusses alternative approaches for dealing with inconsistencies in the knowledge base. In addition, for efficiency, we implemented techniques called extensionalization, avoiding reanalysis, and code minimization.

A Design for Additive Manufacturing Ontology

2016 ◽  
Author(s):  
Mahmoud Dinar ◽  
David W. Rosen
Keyword(s):  
Additive Manufacturing ◽  
Knowledge Base ◽  
System Integration ◽  
Domain Knowledge ◽  
Description Logic ◽  
Design For Additive Manufacturing ◽  
Traditional Design ◽  
Subtractive Manufacturing ◽  
Future Work

Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal OWL/RDF representations in the Protégé tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark studies. This is demonstrated in a case study with three design features: revolute joint, thread assembly (screw connection), and slider-crank. How multiple instances (build events) are stored and retrieved in the knowledge base is discussed in light of modeling requirements for the DFAM knowledge base: knowledge capture and reuse, supporting a tutoring system, integration into CAD tools. A set of competency questions are described to evaluate knowledge retrieval. Examples are given with SPARQL queries. Knowledge documentation is the main objective of the current ontology. However, description logic creates multiple opportunities for future work, including representing and reasoning about DFAM rules in a structured modular hierarchy, discovering new rules with induction, and recognizing patterns with classification, e.g., what leads to “successful” vs. “unsuccessful” fabrications.

A Prioritized Default Extension to Description Logic Knowledge Base

2008 ◽  
Author(s):  
Shaohua Liu ◽  
Junsheng Yu ◽  
Yinglong Ma ◽  
Bing Xu ◽  
Yuan Mai ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Description Logic

An Ontology-Based Information Extraction System for Organic Farming

2021 ◽  
Vol 17 (2) ◽  
pp. 79-99
Author(s):  
Adebayo Adewumi Abayomi-Alli ◽  
Oluwasefunmi 'Tale Arogundade ◽  
Sanjay Misra ◽  
Mulkah Opeyemi Akala ◽  
Abiodun Motunrayo Ikotun ◽  
...  
Keyword(s):  
Information Extraction ◽  
Knowledge Base ◽  
Organic Farming ◽  
Description Logic ◽  
Query Language ◽  
Relevant Information ◽  
Extraction System ◽  
Ontology Development ◽  
Ontology Language ◽  
Information Extraction System

In the existing farming system, information is obtained manually, and most times, farmers act based on their discretion. Sometimes, farmers rely on information from experts and extension officers for decision making. In recent times, a lot of information systems are available with relevant information on organic farming practices; however, such information is scattered in different context, form, and media all over the internet, making their retrieval difficult. The use of ontology with the aid of a conceptual scheme makes the comprehensive and detailed formalization of any subject domain possible. This study is aimed at acquiring, storing, and providing organic farming-based information available to current and intending software developer who may wish to develop applications for farmers. It employs information extraction (IE) and ontology development techniques to develop an ontology-based information extraction (OBIE) system called ontology-based information extraction system for organic farming (OBIESOF). The knowledge base was built using protégé editor; Java was used for the implementation of the ontology knowledge base with the aid of the high-level application programming language for working web ontology language application program interface (OWL API). In contrast, HermiT was used to checking the consistencies of the ontology and for submitting queries in order to verify their validity. The queries were expressed in description logic (DL) query language. The authors tested the capability of the ontology to respond to user queries by posing instances of the competency questions from DL query interface. The answers generated by the ontology were promising and serve as positive pointers to its usefulness as a knowledge repository.

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