scholarly journals Ontology merging as social choice: judgment aggregation under the open world assumption

2012 ◽  
Vol 24 (6) ◽  
pp. 1229-1249 ◽  
Author(s):  
D. Porello ◽  
U. Endriss
Keyword(s):  
Social Choice ◽  
Judgment Aggregation ◽  
Ontology Merging ◽  
Open World ◽  
Open World Assumption

scholarly journals Incomplete Information Management Using an Improved Belief Entropy in Dempster-Shafer Evidence Theory

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 993 ◽  
Author(s):  
Bin Yang ◽  
Dingyi Gan ◽  
Yongchuan Tang ◽  
Yan Lei
Keyword(s):  
Data Fusion ◽  
Incomplete Information ◽  
Information Fusion ◽  
Evidence Theory ◽  
Sensor Data ◽  
Uncertain Information ◽  
Open World ◽  
Belief Entropy ◽  
Open World Assumption ◽  
Deng Entropy

Quantifying uncertainty is a hot topic for uncertain information processing in the framework of evidence theory, but there is limited research on belief entropy in the open world assumption. In this paper, an uncertainty measurement method that is based on Deng entropy, named Open Deng entropy (ODE), is proposed. In the open world assumption, the frame of discernment (FOD) may be incomplete, and ODE can reasonably and effectively quantify uncertain incomplete information. On the basis of Deng entropy, the ODE adopts the mass value of the empty set, the cardinality of FOD, and the natural constant e to construct a new uncertainty factor for modeling the uncertainty in the FOD. Numerical example shows that, in the closed world assumption, ODE can be degenerated to Deng entropy. An ODE-based information fusion method for sensor data fusion is proposed in uncertain environments. By applying it to the sensor data fusion experiment, the rationality and effectiveness of ODE and its application in uncertain information fusion are verified.

Approaches to Semantics in Knowledge Management

2009 ◽  
pp. 257-281
Author(s):  
Cristiano Fugazza ◽  
Stefano David ◽  
Anna Montesanto ◽  
Cesare Rocchi
Keyword(s):  
Neural Networks ◽  
Knowledge Management ◽  
Artificial Neural Networks ◽  
Database Management ◽  
Description Logics ◽  
Open World ◽  
Open World Assumption ◽  
Relational Database Management ◽  
Static Nature ◽  
Relational Database Management Systems

There are different approaches to modeling a computational system, each providing different semantics. We present a comparison among different approaches to semantics and we aim at identifying which peculiarities are needed to provide a system with uniquely interpretable semantics. We discuss different approaches, namely, Description Logics, Artificial Neural Networks, and relational database management systems. We identify classification (the process of building a taxonomy) as common trait. However, in this chapter we also argue that classification is not enough to provide a system with a Semantics, which emerges only when relations among classes are established and used among instances. Our contribution also analyses additional features of the formalisms that distinguish the approaches: closed versus. open world assumption, dynamic versus. static nature of knowledge, the management of knowledge, and the learning process.

scholarly journals Adapted Rules for UML Modelling of Geospatial Information for Model-Driven Implementation as OWL Ontologies

2019 ◽  
Vol 8 (9) ◽  
pp. 365 ◽  
Author(s):  
Jetlund ◽  
Onstein ◽  
Huang
Keyword(s):  
Spatial Information ◽  
Unified Modeling Language ◽  
Transport Systems ◽  
Geospatial Information ◽  
Unified Modeling ◽  
Model Driven ◽  
Open World ◽  
Ontology Language ◽  
Data Files ◽  
Open World Assumption

This study aims to improve the implementation of models of geospatial information in Web Ontology Language (OWL). Large amounts of geospatial information are maintained in Geographic Information Systems (GIS) based on models according to the Unified Modeling Language (UML) and standards from ISO/TC 211 and the Open Geospatial Consortium (OGC). Sharing models and geospatial information in the Semantic Web will increase the usability and value of models and information, as well as enable linking with spatial and non-spatial information from other domains. Methods for conversion from UML to OWL for basic concepts used in models of geospatial information have been studied and evaluated. Primary conversion challenges have been identified with specific attention to whether adapted rules for UML modelling could contribute to improved conversions. Results indicated that restrictions related to abstract classes, unions, compositions and code lists in UML are challenging in the Open World Assumption (OWA) on which OWL is based. Two conversion challenges are addressed by adding more semantics to UML models: global properties and reuse of external concepts. The proposed solution is formalized in a UML profile supported by rules and recommendations and demonstrated with a UML model based on the Intelligent Transport Systems (ITS) standard ISO 14825 Geographic Data Files (GDF). The scope of the resulting ontology will determine to what degree the restrictions shall be maintained in OWL, and different conversion methods are needed for different scopes.

scholarly journals Belief Merging and Judgment Aggregation in Fuzzy Setting

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Ismat Beg ◽  
Nabeel Butt
Keyword(s):  
Fuzzy Logic ◽  
Social Choice ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Judgment Aggregation ◽  
Belief Merging ◽  
Aggregation Functions ◽  
Fuzzy Aggregation ◽  
Doctrinal Paradox ◽  
Fuzzy Setting

We explore how judgment aggregation and belief merging in the framework of fuzzy logic can help resolve the “Doctrinal Paradox.” We also illustrate the use of fuzzy aggregation functions in social choice theory.

scholarly journals Neutrality and relative acceptability in judgment aggregation

2019 ◽  
Vol 55 (1) ◽  
pp. 25-49
Author(s):  
Zoi Terzopoulou ◽  
Ulle Endriss
Keyword(s):  
Social Choice ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Practical Interest ◽  
Judgment Aggregation ◽  
Aggregation Rule ◽  
Impossibility Theorem ◽  
Collective Acceptance ◽  
Special Case

AbstractOne of the fundamental normative principles in social choice theory is that of neutrality. In the context of judgment aggregation, neutrality is encoded in the form of an axiom expressing that, when two possible judgments enjoy the same support amongst the individuals, then either both or neither of them should be accepted. This is a reasonable requirement in many scenarios. However, we argue that for scenarios in which individuals are asked to pass judgment on very diverse kinds of propositions, a notion of relative acceptability is better suited. We capture this notion by a new axiom that hinges on a binary “acceptability” relation A between propositions: if a given coalition accepting a proposition p entails the collective acceptance of p, then the same should be true for every other proposition q related to p via A. Intuitively, pAq means that p is at least as acceptable as q. Classical neutrality is then a special case where all propositions are equally acceptable. We show that our new axiom allows us to circumvent a classical impossibility theorem in judgment aggregation for certain scenarios of practical interest. Also, we offer a precise characterisation of all scenarios that are safe, in the sense that any aggregation rule respecting the relative acceptability between propositions will always return logically consistent outcomes.

Reasoning with Vague Concepts in Description Logics

2017 ◽  
Vol 6 (2) ◽  
pp. 43-58
Author(s):  
Mohamed Gasmi ◽  
Mustapha Bourahla
Keyword(s):  
Description Logics ◽  
Formal Languages ◽  
The Third ◽  
Open World ◽  
Tableau Algorithm ◽  
Vague Concept ◽  
Open World Assumption

The open world assumption in ontologies representing knowledge may assign deficient (imprecise) meaning for ontology concepts which are language adjectives referring the meaning of classes of objects (individuals). The interpretation of an imprecise (vague) concept is by three subsets of individuals. The first subset of individuals surely belongs to the vague concept, the second subset of individuals surely doesn't belong the vague concept and the third subset is in the borderline. In this paper, the authors will show that is possible to describe ontology vague concepts using well-defined formal languages. The authors will propose also an extension of the Tableau algorithm for reasoning over vague ontologies.

A Dualism Based Semantics Formalization Mechanism for Model Driven Engineering

2009 ◽  
Vol 1 (4) ◽  
pp. 90-110 ◽  
Author(s):  
Yucong Duan
Keyword(s):  
Theoretical Investigation ◽  
Context Sensitivity ◽  
Software Implementation ◽  
Model Driven Engineering ◽  
Closed World Assumption ◽  
Model Driven ◽  
Open World ◽  
Closed World ◽  
Open World Assumption ◽  
Measure Evaluation

Firstly this article presents a thorough discussion of semantics formalization related issues in model driven engineering (MDE). Then motivated for the purpose of software implementation, and attempts to overcome the shortcomings of incompleteness and context-sensitivity in the existing models, we propose to study formalization of semantics from a cognitive background. Issues under study cover the broad scope of overlap vs. incomplete vs. complete, closed world assumption (CWA) vs. open world assumption (OWA), Y(Yes)/N(No) vs. T(True)/F(False), subjective (SUBJ) vs. objective (OBJ), static vs. dynamic, unconsciousness vs. conscious, human vs. machine aspects, and so forth. A semantics formalization approach called EID-SCE (Existence Identification Dualism-Semantics Cosmos Explosion) is designed to meet both the theoretical investigation and implementation of the proposed formalization goals. EID-SCE supports the measure/evaluation in a {complete, no overlap} manner whether a given concept or feature is an improvement. Some elementary cases are also shown to demonstrate the feasibility of EID-SCE.

Using the Semantic Web Rule Language in the Development of Ontology-Driven Applications

2010 ◽  
pp. 525-539 ◽  
Author(s):  
Martin O’Connor ◽  
Mark Musen ◽  
Amar Das
Keyword(s):  
Semantic Web ◽  
Description Logic ◽  
Deductive Reasoning ◽  
Description Logics ◽  
Open World ◽  
Closed World ◽  
Amount Of Knowledge ◽  
Open World Assumption ◽  
Formal Characteristic ◽  
Semantic Web Rule Language

The Semantic Web Rule Language (SWRL) is an expressive OWL-based rule language. SWRL allows users to write Horn-like rules that can be expressed in terms of OWL concepts to provide more powerful deductive reasoning capabilities than OWL alone. Semantically, SWRL is built on the same description logic foundation as OWL and provides similar strong formal guarantees when performing inference. Due to its description logics foundation, rule-based applications developed using SWRL have a number of relatively novel characteristics. For example, SWRL shares OWL’s open world assumption so certain types of rules that assume a closed world may be difficult or impossible to write in SWRL. In addition, all inference in SWRL is monotonic so deductions cannot be updated or retracted. These formal characteristic have a strong influence on the development and use of SWRL rules in ontology-driven applications. In this chapter, we describe the primary features of SWRL and outline how, despite some limitations, SWRL can be used to dramatically increase amount of knowledge that be represented in OWL ontologies.

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