Description Logic Research Articles

Bayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompleteness.

The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain.

Math Word Problem Generation via Disentangled Memory Retrieval

The task of math word problem (MWP) generation, which generates an MWP given an equation and relevant topic words, has increasingly attracted researchers’ attention. In this work, we introduce a simple memory retrieval module to search related training MWPs, which are used to augment the generation. To retrieve more relevant training data, we also propose a disentangled memory retrieval module based on the simple memory retrieval module. To this end, we first disentangle the training MWPs into logical description and scenario description and then record them in respective memory modules. Later, we use the given equation and topic words as queries to retrieve relevant logical descriptions and scenario descriptions from the corresponding memory modules, respectively. The retrieved results are then used to complement the process of the MWP generation. Extensive experiments and ablation studies verify the superior performance of our method and the effectiveness of each proposed module. The code is available at https://github.com/mwp-g/MWPG-DMR .

Stable Model Semantics for Description Logic Terminologies

This paper studies a stable model semantics for Description Logic (DL) knowledge bases (KBs) and for (possibly cyclic) terminologies, ultimately showing that terminologies under the proposed semantics can be equipped with effective reasoning algorithms. The semantics is derived using Quantified Equilibrium Logic, and---in contrast to the usual semantics of DLs based on classical logic---supports default negation and allows to combine the open-world and the closed-world assumptions in a natural way. Towards understanding the computational properties of this and related formalisms, we show a strong undecidability result that applies not only to KBs under the stable model semantics, but also to the more basic setting of minimal model reasoning. Specifically, we show that concept satisfiability in minimal models of an ALCIO KB is undecidable. We then turn our attention to (possibly cyclic) DL terminologies, where ontological axioms are limited to definitions of concept names in terms of complex concepts. This restriction still yields a very rich setting. We show that standard reasoning problems, like concept satisfiability and subsumption, are ExpTime-complete for terminologies expressed in ALCI under the stable model semantics.

A fuzzy description logic based IoT framework: Formal verification and end user programming.

The Internet of Things (IoT) has become one of the most popular technologies in recent years. Advances in computing capabilities, hardware accessibility, and wireless connectivity make possible communication between people, processes, and devices for all kinds of applications and industries. However, the deployment of this technology is confined almost entirely to tech companies, leaving end users with only access to specific functionalities. This paper presents a framework that allows users with no technical knowledge to build their own IoT applications according to their needs. To this end, a framework consisting of two building blocks is presented. A friendly interface block lets users tell the system what to do using simple operating rules such as "if the temperature is cold, turn on the heater." On the other hand, a fuzzy logic reasoner block built by experts translates the ambiguity of human language to specific actions to the actuators, such as "call the police." The proposed system can also detect and inform the user if the inserted rules have inconsistencies in real time. Moreover, a formal model is introduced, based on fuzzy description logic, for the consistency of IoT systems. Finally, this paper presents various experiments using a fuzzy logic reasoner to show the viability of the proposed framework using a smart-home IoT security system as an example.

Evaluating Datalog Tools for Meta-reasoning over OWL 2 QL

Abstract Metamodeling is a general approach to expressing knowledge about classes and properties in an ontology. It is a desirable modeling feature in multiple applications that simplifies the extension and reuse of ontologies. Nevertheless, allowing metamodeling without restrictions is problematic for several reasons, mainly due to undecidability issues. Practical languages, therefore, forbid classes to occur as instances of other classes or treat such occurrences as semantically different objects. Specifically, meta-querying in SPARQL under the Direct Semantic Entailment Regime uses the latter approach, thereby effectively not supporting meta-queries. However, several extensions enabling different metamodeling features have been proposed over the last decade. This paper deals with the Metamodeling Semantics (MS) over OWL 2 QL and the Metamodeling Semantic Entailment Regime (MSER), as proposed in Lenzerini et al. (2015, Description Logics) and Lenzerini et al. (2020, Information Systems 88, 101294), Cima et al. (2017, Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, 1–6). A reduction from OWL 2 QL to Datalog for meta-querying was proposed in Cima et al. (2017, Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, 1–6). In this paper, we experiment with various logic programming tools that support Datalog querying to determine their suitability as back-ends to MSER query answering. These tools stem from different logic programming paradigms (Prolog, pure Datalog, Answer Set Programming, Hybrid Knowledge Bases). Our work shows that the Datalog approach to MSER querying is practical also for sizeable ontologies with limited resources (time and memory). This paper significantly extends Qureshi and Faber (2021, International Joint Conference on Rules and Reasoning, Springer, 218–233.) by a more detailed experimental analysis and more background.

First-Order Temporal Logic on Finite Traces: Semantic Properties, Decidable Fragments, and Applications

Formalisms based on temporal logics interpreted over finite strict linear orders, known in the literature as finite traces , have been used for temporal specification in automated planning, process modelling, (runtime) verification and synthesis of programs, as well as in knowledge representation and reasoning. In this paper, we focus on first-order temporal logic on finite traces . We first investigate preservation of equivalences and satisfiability of formulas between finite and infinite traces, by providing a set of semantic and syntactic conditions to guarantee when the distinction between reasoning in the two cases can be blurred. Moreover, we show that the satisfiability problem on finite traces for several decidable fragments of first-order temporal logic is ExpSpace -complete, as in the infinite trace case, while it decreases to NExpTime when finite traces bounded in the number of instants are considered. This leads also to new complexity results for temporal description logics over finite traces. Finally, we investigate applications to planning and verification, in particular by establishing connections with the notions of insensitivity to infiniteness and safety from the literature. Linear temporal logic over finite traces is used as a formalism for temporal specification in automated planning, process modelling and (runtime) verification. In this paper, we investigate first-order temporal logic over finite traces, lifting some known results to a more expressive setting. Satisfiability in the two-variable monodic fragment is shown to be ExpSpace -complete, as for the infinite trace case, while it decreases to NExpTime when we consider finite traces bounded in the number of instants. This leads to new complexity results for temporal description logics over finite traces. We further investigate satisfiability and equivalences of formulas under a model-theoretic perspective, providing a set of semantic conditions that characterise when the distinction between reasoning over finite and infinite traces can be blurred. Finally, we apply these conditions to planning and verification.

Ontology of active and passive environmental exposure

Exposure is a central concept of the health and behavioural sciences needed to study the influence of the environment on the health and behaviour of people within a spatial context. While an increasing number of studies measure different forms of exposure, including the influence of air quality, noise, and crime, the influence of land cover on physical activity, or of the urban environment on food intake, we lack a common conceptual model of environmental exposure that captures its main structure across all this variety. Against the background of such a model, it becomes possible not only to systematically compare different methodological approaches but also to better link and align the content of the vast amount of scientific publications on this topic in a systematic way. For example, an important methodical distinction is between studies that model exposure as an exclusive outcome of some activity versus ones where the environment acts as a direct independent cause (active vs. passive exposure). Here, we propose an information ontology design pattern that can be used to define exposure and to model its variants. It is built around causal relations between concepts including persons, activities, concentrations, exposures, environments and health risks. We formally define environmental stressors and variants of exposure using Description Logic (DL), which allows automatic inference from the RDF-encoded content of a paper. Furthermore, concepts can be linked with data models and modelling methods used in a study. To test the pattern, we translated competency questions into SPARQL queries and ran them over RDF-encoded content. Results show how study characteristics can be classified and summarized in a manner that reflects important methodical differences.

Expressiveness of SHACL Features and Extensions for Full Equality and Disjointness Tests

SHACL is a W3C-proposed schema language for expressing structural constraints on RDF graphs. Recent work on formalizing this language has revealed a striking relationship to description logics. SHACL expressions can use three fundamental features that are not so common in description logics. These features are equality tests; disjointness tests; and closure constraints. Moreover, SHACL is peculiar in allowing only a restricted form of expressions (so-called targets) on the left-hand side of inclusion constraints. The goal of this paper is to obtain a clear picture of the impact and expressiveness of these features and restrictions. We show that each of the four features is primitive: using the feature, one can express boolean queries that are not expressible without using the feature. We also show that the restriction that SHACL imposes on allowed targets is inessential, as long as closure constraints are not used. In addition, we show that enriching SHACL with "full" versions of equality tests, or disjointness tests, results in a strictly more powerful language.

Improving the interoperability of drugs terminologies: Infusing local standardization with an international perspective

Objectives:The objective of this study is to describe how OCRx (Canadian Drug Ontology) has been built to address the dual need for local drug information integration in Canada and alignment with international standards requirements. Methods:This paper delves into (i) the implementation efforts to meet the Identification of Medicinal Product (IDMP) requirements in OCRx, alongside the ontology update strategy, (ii) the structure of the ontology itself, (iii) the alignment approach with several reference Knowledge Organization Systems, including SNOMED CT, RxNorm, and the list of “Code Identifiant de Spécialité” (CIS-Code), and (iv) the look-up services developed to facilitate its access and utilization. Results:Each OCRx release contains two distinct versions: the full and the up-to-date version. The full version encompasses all drugs with a DIN code sanctioned by Health Canada, while the up-to-date version is limited to drugs currently marketed in Canada. In the last release of OCRx, the full version comprises 162,400 classes; meanwhile, the up-to-date version consists of 36,909 classes. In terms of mappings with OCRx, substances in RxNorm and SNOMED CT fall below 40%, registering at 37% and 22% respectively. Meanwhile, mappings for CIS-Code achieve coverage of 61%. The strength mappings are notably low for RxNorm at 40% and for CIS-code at 28%. This affects the mapping of clinical drugs, which are predominantly alignable through post-coordinated expressions: 56% for RxNorm, 80% for SNOMED CT, and 35% for CIS-Code. The main support service of OCRx is a look-up service known as PaperRx that displays OCRx’s entities based on description logic queries (DL-queries) performed through the classified structure of OCRx. The look-up services also contain a SPARQL endpoint, an OCRx OWL file downloader, and a RESTful API. Discussion:The OCRx ontology demonstrates a significant effort towards integrating Canadian drug information with international standards. However, there are areas for improvement. In the future, our focus will be on refining the structure of OCRx for better classification capability and improvement of dosage conversion. Additionally, we aim to harness OCRx in constructing an ontology-based annotator, setting our sights on its deployment in real-world data integration scenarios.

Minimizing fuzzy interpretations in fuzzy description logics by using crisp bisimulations

The problem of minimizing finite fuzzy interpretations in fuzzy description logics (FDLs) is worth studying. For example, the structure of a fuzzy/weighted social network can be treated as a fuzzy interpretation in FDLs, where actors are individuals and actions are roles. Minimizing the structure of a fuzzy/weighted social network makes it more compact, thus making network analysis tasks more efficient. In this work, we study the problem of minimizing a finite fuzzy interpretation in a FDL by using the largest crisp auto-bisimulation. The considered FDLs use the Baaz projection operator and their semantics is specified using an abstract algebra of fuzzy truth values, which can be any linear and complete residuated lattice. We provide an efficient algorithm with a complexity of O((mlog⁡l+n)log⁡n) for minimizing a given finite fuzzy interpretation I, where n is the size of the domain of I, m is number of nonzero instances of atomic roles of I and l is the number of different fuzzy values used for instances of atomic roles of I. We prove that the fuzzy interpretation returned by the algorithm is minimal among the ones that preserve fuzzy TBoxes and ABoxes under certain conditions.

A Tolerance Specification Automatic Design Method for Screening Geometric Tolerance Types

At present, the automatic generation of tolerance types based on rule-based reasoning has an obvious characteristic: for the same assembly feature, tolerance items are recommended that satisfy all feature characteristics, with a large number of recommendations. For this reason, automatically selecting tolerance types and reducing designer autonomy remains a challenging task, especially for complex mechanical products designed using heterogeneous CAD systems. This article proposes a tolerance specification design method for the automatic selection of assembly tolerance types. Based on the construction of a hierarchical representation model of assembly tolerance information with tolerance-zone degrees of freedom (DOFs), a semantic model of geometric tolerance information with tolerance-zone DOFs and a meta-ontology model of assembly tolerance information representation are constructed. Descriptive logic is used to express the attribute relationships between different classes in the assembly tolerance information meta-ontology model, and screening inference rules are constructed based on the mechanism for selecting assembly tolerance types based on tolerance-zone DOFs. On this basis, a process for selecting assembly geometric tolerance types based on the ontology of tolerance-zone DOFs is formed. Finally, the effectiveness and feasibility of this method were verified through examples.

Semantics of Belief Change Operators for Intelligent Agents

AbstractThis paper summarises several contributions to the theory of belief change by the authors’ dissertation thesis. First, a relational characterization of belief revision for Tarskian logics is considered, encompassing first-order predicate logic, description logic, modal logics and many monotonic logics with model-theoretic semantics. Those logics where total preorders are the standard semantics for revision are characterized. The second contribution considered is a theory of belief revision that builds upon the idea that agents are limited in what the outcome of a revision is. Furthermore, advancements in principles for iterated belief contraction given in the thesis are outlined.

The RDF2vec family of knowledge graph embedding methods

Knowledge graph embeddings represent a group of machine learning techniques which project entities and relations of a knowledge graph to continuous vector spaces. RDF2vec is a scalable embedding approach rooted in the combination of random walks with a language model. It has been successfully used in various applications. Recently, multiple variants to the RDF2vec approach have been proposed, introducing variations both on the walk generation and on the language modeling side. The combination of those different approaches has lead to an increasing family of RDF2vec variants. In this paper, we evaluate a total of twelve RDF2vec variants on a comprehensive set of benchmark models, and compare them to seven existing knowledge graph embedding methods from the family of link prediction approaches. Besides the established GEval benchmark introducing various downstream machine learning tasks on the DBpedia knowledge graph, we also use the new DLCC (Description Logic Class Constructors) benchmark consisting of two gold standards, one based on DBpedia, and one based on synthetically generated graphs. The latter allows for analyzing which ontological patterns in a knowledge graph can actually be learned by different embedding. With this evaluation, we observe that certain tailored RDF2vec variants can lead to improved performance on different downstream tasks, given the nature of the underlying problem, and that they, in particular, have a different behavior in modeling similarity and relatedness. The findings can be used to provide guidance in selecting a particular RDF2vec method for a given task.

Natural Language Generation and Parsing as Heuristic Planning Problems

This paper formulates the problems of natural language generation and parsing as particular instances of the classical planning problem. It assumes the existence of a Categorial Grammar lexicon from which the preconditions and effects of available actions are obtained. A declarative formalization of heuristics for action selection is used to guide the search for solutions. Heuristics for mapping formulas in the description logic DL-Lite (R,and) into English sentences and backwards, and examples of application to Human Robot Interaction (HRI) are presented to illustrate the effectiveness of the approach.

Computing crisp bisimulations for fuzzy structures

We present an efficient algorithm for computing the partition corresponding to the greatest crisp bisimulation of a given finite fuzzy labeled graph. Its complexity is of order O((mlog⁡l+n)log⁡n), where n, m and l are the number of vertices, the number of nonzero edges and the number of different fuzzy degrees of edges of the input graph, respectively. We also study a similar problem for the setting with counting successors, which corresponds to the case with qualified number restrictions in description logics and graded modalities in modal logics. In particular, we provide an efficient algorithm with the complexity O((mlog⁡m+n)log⁡n) for the considered problem in that setting.

Verbalisation of an alternative academic position in totalitarian discourse

Background. In Soviet Ukraine, academic discourse often acted as a means of implementing language planning, in particular as a tool for the transformation of the language corpus. All grammar textbooks published after 1933 broadcast the official knowledge: the vocative is not a full-fledged case, but rather a special form of address; morphological means of expressing address in Ukrainian are the “vocative form” and “nominative case.” In the conditions of total control over all areas of social life, Ukrainian linguists were faced with a choice of either 1) look for certain language devices, broadcasting the official theory, which would convince the addressee to believe in the talking points that did not fully comply with the language facts, and then anchor those points in their consciousness; 2) avoid aspects that disagree with the language practice or the logic of academic description; 3) word the findings of their research and observations of the language practice in a way that would not contradict the official theory.Contribution to the research field. The article is dedicated to the analysis of the communication practices used by Ukrainian linguists in the Soviet times to express their academic position, which did not agree with official knowledge. The object of comprehension was a unique for postcolonial societies situation in which the creators of both the official discourse and the alternative discourse opposed to it were the colonised themselves.Purpose. The aim of this research is to analyse ways and means of verbalisation of the alternative academic position held by linguists in the academic discourse of the totalitarian era, based on the materials representing the topics “The Case System” and “Address” in Ukrainian grammar books for higher education, published between 1933–1991.Methods. The research is based on the theoretical and methodological foundations of postcolonial studies, which involve a critical reading of texts that reflect the influence of various forms of authority on the life of subordinate communities. In particular, the theory of critical reading of J. Errimgton’s linguistic works and R. Vodaks’ methodology of discourse-historical approach, which has been adapted for academic discourse analysis, have been applied in this research.Results. Some linguists, who did not share the canonised theory of the vocative, implied their point of view in the official texts they had created (i.e. textbooks for higher education.) On the one hand, they used official terminology and theoretical concepts: they were consistent in naming the vocative case a “vocative form,” and presented two ways of expressing address. On the other hand, the lexical and grammatical structure of their statements levelled the postulates regarding the fact that “vocative is not a case”, and that “the nominative case is used to express address on par with the vocative.” Among the techniques used by the linguists, heavily euphemistic speech in combination with syntactic complication of the structure prevailed, as well as splitting nominations by verbalising the concept with variant naming and violation of logical connections between consecutive statements. Such individual practices of linguistic resistance replicated the practices of the official totalitarian discourse, but with the aim to broadcast the opposite meaning.Discussion. The peculiarity of the alternative academic discourse (in particular, the language education one) of the totalitarian era lies in the fact that it did not directly confront the official theory, but rather occurred within its boundaries. This gives a reason to consider some Ukrainian linguists of the Soviet period as creators of both colonial and anti-colonial discourses.

‘Immediacy’ in Whitehead and Blaga

In Whitehead’s metaphysics there is a concept of ‘immediacy’ which is interesting to interpret in relation to the concept of ‘immediacy’ found in Lucian Blaga’s metaphysics. Immediacy stands in opposition to the wholeness of existence and the complexity of reality in both thinkers. In Whitehead, immediate experience is merely a facet of the constructed series of events and processes fundamental for existence and reality and for connecting our objective, scientific and logical descriptions of the world, and the more everyday world of subjective experience. In Blaga, immediacy is the label for limited (animal-like) existence deprived of the metaphysical dimension. However, in Blaga, man is defined by the metaphysical dimension and thus, in terms closer to Whitehead’s view, always engaged in a crusade to comprehend both ‘physical multiplicity’ (the World) and ‘the infinite ground of all mentality’ (God), which is consonant with Blaga’s concept of man’s defining situation within ‘the horizon of mystery’. Both metaphysics accepted a perspective, or, an interpretation of the idea that God creates the World as well as the World creating God. In our view, the Unmoved Mover image of God remains as a ‘trace’ in the idea of permanent reference for the World. This is comparable with the perspective found in the metaphysics of Lucian Blaga, where the metaphysical center, the ‘Great Anonymous,’ ‘pushes’ backwards the human being, via limitative ‘divine differentials’ occasioning the limiting stylistic matrices for the creative and intrusive ontological and metaphysical drive of man.

Ontological analysis in the problems of container applications threat modelling

Objectives. The main purpose of the work is the experimental verification of the method of automatic threat modelling based on the ontological approach using the example of multicomponent container applications presented in the form of data flow diagrams.Methods. Methods of ontological modelling and knowledge management are used in the work. The Web Ontology Language is used to represent knowledge; automatic reasoning based on description logics is used for threat modelling.Results. A machine-readable set (dataset) of 200 data flow diagrams is developed; each diagram is obtained from the configuration of a real container application and is presented as an ontology and a knowledge graph. An ontological two-level domain-specific threat model of container applications is formed. An experiment is conducted to compare the coverage by threats using the common approach and using domain-specific threats for created dataset. For 95 % of the diagrams, the domain-specific threat model showed the coverage similar or greater than the common approach.Conclusion. The results of the experiment prove the suitability and effectiveness of the ontological approach for automatic threat modelling. The created dataset can be used for various research in the field of automation of threat modelling.

RESEARCH AND DESIGN OF THE MARKETING CLOUD SALESFORCE CRM ARCHITECTURE DEPENDING ON THE COMPANY'S MARKETING STRATEGY

The purpose of the study is to increase the level of effective attraction of new customers and retention of the company's existing customer base through the implementation of innovative marketing strategies. The expediency of using the concept of customer relationship management (CRM) and the use of CRM-class information systems to achieve the goal has been proven. The CRM platform Salesforce Marketing Cloud, which belongs to cloud types of information systems, was studied. A description of the Salesforce Marketing Cloud business logic is given, which includes decision-making based on analytical data, customer segmentation, automation of an individual approach to customers with the aim of increasing customer loyalty and increasing company revenue. Salesforce Marketing Cloud provides an opportunity to create and manage personalized marketing activities, interact with customers through various channels, analyze the effects of marketing efforts for continuous improvement of the company's marketing strategies. The functionality and features of the main components of Salesforce Marketing Cloud were studied. Salesforce Marketing Cloud allows you to effectively manage email marketing, mobile marketing, social media campaigns and other types of marketing. Salesforce Marketing Cloud empowers companies to create and manage personalized marketing efforts, engage with customers across multiple channels, and analyze their marketing efforts for continuous improvement. Salesforce Marketing Cloud architecture was designed for behavioral segmentation of the company's customers. A web application has been developed to improve the platform users' experience with customer data stored in Data Extensions. To automate customer segmentation based on their behavioral data, Automation Studio was used, SQL queries were built, and Data Views system data tables were used. The developed architecture of Marketing Cloud Salesforce CRM based on behavioral segmentation is an important tool for the implementation of the company's marketing strategy, ensuring the successful attraction and retention of customers, as well as for achieving strategic goals.

Conjunctive query answering over unrestricted OWL 2 ontologies

Conjunctive Query (CQ) answering is a primary reasoning task over knowledge bases. However, when considering expressive description logics, query answering can be computationally very expensive; reasoners for CQ answering, although heavily optimized, often sacrifice expressive power of the input ontology or completeness of the computed answers in order to achieve tractability and scalability for the problem. In this work, we present a hybrid query answering architecture that combines various services to provide a CQ answering service for OWL. Specifically, it combines scalable CQ answering services for tractable languages with a CQ answering service for a more expressive language approaching the full OWL 2. If the query can be fully answered by one of the tractable services, then that service is used, to ensure maximum performance. Otherwise, the tractable services are used to compute lower and upper bound approximations. The union of the lower bounds and the intersection of the upper bounds are then compared. If the bounds do not coincide, then the “gap” answers are checked using the “full” service. These techniques led to the development of two new systems: (i) RSAComb, an efficient implementation of a new tractable answering service for RSA (role safety acyclic) (ii) ACQuA, a reference implementation of the proposed hybrid architecture combining RSAComb, PAGOdA, and HermiT to provide a CQ answering service for OWL. Our extensive evaluation shows how the additional computational cost introduced by reasoning over a more expressive language like RSA can still provide a significant improvement compared to relying on a fully-fledged reasoner. Additionally, we show how ACQuA can reliably match the performance of PAGOdA, a state-of-the-art CQ answering system that uses a similar approach, and can significantly improve performance when PAGOdA extensively relies on the underlying fully-fledged reasoner.