Giorgos Stoilos

Huawei Technologies · Department of R&D

Query rewriting is a prominent reasoning technique in ontology-based data access applications. A wide variety of query rewriting algorithms have been proposed in recent years and implemented in highly optimised reasoning sys-tems. Query rewriting systems are complex software pro-grams; even if based on provably correct algorithms, sophis-ticated op...

A large number of conceptually different medical coding and classification systems are in use in medical practice, of which the most popular are ICD-9, ICD-10, and Read Codes. To achieve interoperability, a platform that enables translation between them is needed. In this paper we report on the progress of Babylon Health in developing such an inter...

The success of logic-based methods for comparing entities heavily depends on the axioms that have been described for them in the Knowledge Base (KB). Due to the incompleteness of even large and well engineered KBs, such methods suffer from low recall when applied in real-world use cases. To address this, we designed a reasoning framework that combi...

A wealth of medical knowledge has been encoded in terminologies like SNOMED CT, NCI, FMA, and more. However, these resources are usually lacking information like relations between diseases, symptoms, and risk factors preventing their use in diagnostic or other decision making applications. In this paper we present a pipeline for extracting such inf...

In the current paper we propose a general framework for answering queries over inconsistent DL knowledge bases. The proposed framework considers the ICAR semantics and is based on a rewriting algorithm that can be applied over arbitrary DLs. Since the problem of ICAR-answering is known to be intractable for DLs other than DL-Lite, our algorithm may...

This paper explores how the logical difference between two ontologies can be tracked using a forgetting-based or uniform interpolation (UI)-based approach. The idea is that rather than computing all entailments of one ontology not entailed by the other ontology, which would be computationally infeasible, only the strongest entailments not entailed...

The use of ontologies in applications like dialogue systems, question-answering or decision-support is gradually gaining attention. In such applications, keyword-based user queries are mapped to ontology entities and then the respective application logic is activated. This task is not trivial as user queries may often be vague and imprecise or simp...

An important approach to query answering over description logic (DL) ontologies is via rewriting the input ontology and query into languages such as (disjunctive) datalog, for which scalable data saturation systems exist. This approach has been studied for DLs of different expressivities such as DL-Lite, \(\mathcal {ELHI}\) and Horn-\(\mathcal {SHI...

Inconsistent-tolerant semantics, like the IAR and ICAR semantics, have been proposed as means to compute meaningful query answers over inconsistent Description Logic (DL) ontologies. In the current paper we present a framework for scalable query answering under both the IAR and ICAR semantics , which is based on highly efficient data saturation sys...

Inconsistency-tolerant semantics, like the IAR semantics, have been proposed as means to compute meaningful query answers over inconsistent Description Logic (DL) ontologies. So far query answering under the IAR semantics (IAR-answering) is known to be tractable only for arguably weak DLs like DL-Lite and the quite restricted EL⊥nr fragment of EL⊥....

In previous work we have analysed the infrastructure of the Human Brain Project Medical Informatics Platform focusing on the challenges related to dataintegration based on a visual data exchange tool, called MIPMap. In this paper we present new MIPMap features that enhance the integration process and data access.

Computing a (Union of Conjunctive Queries — UCQ) rewriting ℛ for an input query and ontology and evaluating it over the given dataset is a prominent approach to query answering over ontologies. However, ℛ can be large and complex in structure hence additional techniques, like query subsumption and data constraints, need to be employed in order to m...

Query rewriting is an important technique for answering queries over data described using ontologies. In query rewriting the input, a conjunctive query (CQ) $q$ and an ontology $\mathcal {O}$, is transformed into a new datalog query that captures all answers of $q$ over $\mathcal {O}$ and any dataset $D$. This process can be time-consuming as it is...

Fuzzy extensions to description logics (DLs) have gained considerable attention the last decade. So far most works on fuzzy DLs have focused on either very expressive languages, like fuzzy OWL and OWL 2, or on highly inexpressive ones, like fuzzy OWL 2 QL and fuzzy OWL 2 EL. To the best of our knowledge, a fuzzy extension to the language OWL 2 RL h...

An important approach to query answering over OWL ontologies is via rewriting the input ontology (and query) into a new set of axioms that are expressed in logics for which scalable query answering algorithms exist. This approach has been studied for many important fragments of OWL like , Horn- , OWL 2 QL, and OWL 2 EL. An important family of rewri...

This system description paper introduces the OWL 2 reasoner HermiT. The reasoner is fully compliant with the OWL 2 Direct Semantics as standardised by the World Wide Web Consortium (W3C). HermiT is based on the hypertableau calculus, and it supports a wide range of standard and novel optimisations that improve the performance of reasoning on real-w...

This system description paper introduces the OWL 2 query answering system Hydrowl. Hydrowl is based on novel hybrid techniques which in order to compute the query answers combine at run-time a reasoner ans 1 supporting a (tractable) fragment of OWL 2 (e.g., OWL 2 QL and OWL 2 RL) with a fully-fledged OWL 2 DL reasoner ans 2. The motivation is that...

Fuzzy Description Logics (f-DLs) have been proposed as logical formalisms capable of representing and reasoning with vague/fuzzy information. They are envisioned to be helpful for many applications that need to cope with such type of information such as multimedia processing, decision making, automatic negotiation and more. Recent results have prov...

In previous work it has been shown how an OWL 2 DL ontology \(\mathcal{O}\) can be ‘repaired’ for an OWL 2 RL system ans—that is, how we can compute a set of axioms \(\mathcal{R}\) that is independent from the data and such that ans that is generally incomplete for \(\mathcal{O}\) becomes complete for all SPARQL queries when used with \(\mathcal{O}...

Ontologies expressed in description logics or extensions of datalog are gradually used for describing the domain of many research and industrial strength applications. They provide a formal semantically rich and data-independent layer over which user queries can be posed. A prominent technique for query answering in ontology-based applications is q...

To achieve scalability of query answering, the developers of Semantic Web applications are often forced to use incomplete OWL 2 reasoners, which fail to derive all answers for at least one query, ontology, and data set. The lack of completeness guarantees, however, may be unacceptable for applications in areas such as health care and defence, where...

Query answering over OWL 2 DL ontologies is an important reasoning task for many modern applications. Unfortunately, due to its high computational complexity, OWL 2 DL systems are still not able to cope with datasets containing billions of data. Consequently, application developers often employ provably scalable systems which only support a fragmen...

This volume contains the lecture notes of the 10th Reasoning Web Summer School 2014, held in Athens, Greece, in September 2014. In 2014, the lecture program of the Reasoning Web introduces students to recent advances in big data aspects of semantic web and linked data, and the fundamentals of reasoning techniques that can be used to tackle big data...

One of the most prominent reasoning techniques for query answering is query rewriting. The last years a wide variety of query rewriting systems has been proposed. All of them accept as input a CQ Q and a fixed ontology O and produce a rewriting for Q, O. However, in many real world applications ontologies are very often dynamic—that is, new axioms...

Rewriting-based approaches for answering queries over an OWL 2 DL ontology have so far been developed mainly for Horn fragments of OWL 2 DL. In this paper, we study the possibilities of answering queries over non-Horn ontologies using datalog rewritings. We prove that this is impossible in general even for very simple ontology languages, and even i...

Query rewriting over lightweight ontologies, like DL-Lite ontologies, is a prominent approach for ontology-based data access. It is often the case in realistic scenarios that users ask an initial query which they later refine, e.g., by extending it with new constraints making their initial request more precise. So far, all DL-Lite systems would nee...

Fuzzy Description Logics (fuzzy DLs) are extensions of classic DLs that are capable of representing and reasoning with imprecise and vague knowledge. Though reasoning algorithms for very expressive fuzzy DLs have been developed and optimizations have started to be explored, the efficiency of such systems is still questionable, and the study of trac...

Conjunctive query (CQ) answering is a key reasoning service for ontology-based data access. One of the most prominent approaches to conjunctive query answering is query rewriting where a wide variety of systems has been proposed the last years. All of them accept as input a fixed CQ q and ontology ${\mathcal O}$ and produce a rewriting for $q, {\ma...

Ontology classification—the computation of the subsumption hierarchies for classes and properties—is a core reasoning service provided by all OWL rea-soners known to us. A popular algorithm for computing the class hierarchy is the so-called Enhanced Traversal (ET) algorithm. In this paper we present a new classification algorithm that attempts to a...

The need for scalable query answering often forces Semantic Web applications to use incomplete OWL 2 reasoners, which in some cases fail to derive all answers to a query. This is clearly undesirable, and in some applications may even be unacceptable. To address this problem, we investigate the problem of ‘repairing ’ an ontology T —that is, computi...

This chapter demonstrates how different reasoning algorithms can be applied in multimedia analysis. Extracting semantics from images and videos has proved to be a very difficult task. On the other hand, artificial intelligence has made significant progress in the area of knowledge technologies. The chapter introduces the fuzzy extension of the expr...

Multimedia documents constitute extremely rich information resources, whose efficacious management is intertwined with the effective capturing of the underlying semantics. The conveyed meaning may span along multiple levels and relates to search and retrieval tasks, much as to the very extraction and interpretation of content descriptions. In this...

Largely motivated by Semantic Web applications, many highly scalable, but incomplete, query answering systems have been recently developed. Evaluating the scalability-completeness trade-off exhibited by such systems is an important requirement for many applications. In this paper, we address the problem of formally comparing complete and incomplete...

The pressing need for scalable query answering has motivated the development of many incomplete ontology-based reasoners. Improving the completeness of such systems without sacrificing their favourable performance would be beneficial to many applications. In this paper, we address the following problem: given a query q, a TBox T and an incomplete r...

We extend our recent work on evaluating incomplete reason- ers by introducing strict testing bases. We show how they can be used in practice to identify ontologies and queries where applications can exploit highly scalable incomplete query answering systems while enjoying com- pleteness guarantees normally available only when using computationally...

In this paper, we describe fuzzy CARIN, a knowledge representation language combining fuzzy Description Logics with Horn rules. Fuzzy CARIN integrates the management of fuzzy logic into the non-recursive CARIN language. We introduce the decision problems of answering to conjunctive queries, unions of conjunctive queries and the existential entailme...

Conjunctive query answering is a key reasoning service for many ontology-based applications. In order to improve scalability, many Semantic Web query answering systems give up completeness (i.e., they do not guarantee to return all query answers). It may be useful or even critical to the designers and users of such systems to understand how much an...

The Semantic Web is an extension of the current web, where information would have precisely defined meaning, based on knowledge representation languages. The current W3C standard for representing knowledge is the Web Ontology Language (OWL). OWL is based on Description Logics which is a popular knowledge representation formalism. Although, DLs are...

Sophisticated uncertainty representation and reasoning are necessary for the alignment and integration of Web data from different sources. For this purpose the extension of the Description Logics using fuzzy set theory has been proposed, resulting to fuzzy Description Logics (DLs). However, despite the fact that since the initial proposal a lot of...

Ontology classification—the computation of subsumption hierarchies for classes and properties—is one of the most important tasks for OWL reasoners. Based on the algorithm by Shearer and Horrocks [9], we present a new classification procedure that addresses several open issues of the original algorithm, and that uses several novel optimisations in o...

Conjunctive query answering is a key reasoning service for many ontology-based applications. In order to improve scalability, many Semantic Web query answering systems give up completeness (i.e., they do not guarantee to return all query answers). It may be useful or even critical to the designers and users of such systems to understand how much an...

In the current paper we study the reasoning problem for fuzzy SI (f-SI) under arbitrary continuous fuzzy operators. Our work can be seen as an extension of previous works that studied reasoning algorithms for f-SI, but focused on specific fuzzy operators, e.g. fKD-SI and of reasoning algorithms for less expressive fuzzy DLs, like fL-ALC and fP -ALC...

The last couple of years it is widely acknowledged that uncertainty and fuzzy extensions to ontology languages, like description logics (DLs) and OWL, could play a significant role in the improvement of many Semantic Web (SW) applications like matching, merging and ranking. Unfortunately, existing fuzzy reasoners focus on very expressive fuzzy onto...

The effective management and exploitation of multimedia documents requires the extraction of the underlying semantics. Multimedia analysis algorithms can produce fairly rich, though imprecise information about a multimedia document which most of the times remains unexploited. In this paper we propose a methodology for semantic indexing and retrieva...

Description logics (DLs) are modern knowledge representation formalisms which are used today in many applications for reasoning with structured knowledge. Moreover, they are used in the semantic web (an extension of the current web) through the ontology language OWL. On the other hand fuzzy description logics (fuzzy-DLs) have been proposed as expre...

The RuleML initiative defines a normalized markup for expres sing and exchange rules in the Semantic Web. However, the syntax of the language is still limited and lacks features for representing rule-based languages capable of handling uncertainty and vagueness. It is desirable to have a general extension of RuleML which accommodates major existing...

Fuzzy Description Logics (f-DLs) have been proposed as ex- tensions of classical Description Logics able to handle imprecise and vague knowledge. Although several extensions to expressive DLs have been proposed today and many reasoning algorithms exist there is still no scalable and ecient reasoning system reported, mainly due to inherited computat...

Fuzzy ontologies are envisioned to be useful in the Seman- tic Web. Existing fuzzy ontology reasoners are not scalable enough to handle the scale of data that the Web provides. In this paper, we propose a framework of fuzzy query lan- guages for fuzzy ontologies, and present query answering algorithms for these query languages over fuzzy DL-Lite on...

Fuzzy Description Logics (f-DLs) are extensions of classic DLs that are capable of representing and reasoning about imprecise and vague knowledge. Though reasoning algorithms for very expressive fuzzy DLs have been explored, an open issue in the fuzzy DL community is the study of tractable systems. In this paper we introduce the fuzzy extension of...

Interoperability is a strong requirement in open distributed systems and in the Semantic Web. The need for ontology integration is not always completely met by the available ontology matching techniques because, in most cases, the semantics of the compared ontologies is not considered, thus leading to inconsistent mappings. Probabilistic approaches...

The last couple of years it is widely acknowledged that uncertainty and fuzzy extensions to ontology languages, like Description Logics (DLs) and OWL, could play a significant role in the improvement of many Semantic Web (SW) applications. Many of the tasks of SW like trust, matching, merging, ranking usually involve confidence or truth degrees tha...

The great evolution of ontologies during the last decade, bred the need for storage and querying for the Semantic Web. For that pur- pose, many RDF tools capable of storing a knowledge base, and also performing queries on it, were constructed. Recently, fuzzy extensions to description logics have gained considerable attention especially for the pur...

While knowledge representation languages developed in the context of the Semantic Web build mainly on crisp knowledge, fuzzy reasoning seems to be needed for many applications, e.g. for retrieval of images or other resources. However, techniques for fuzzy reasoning need to scale to large A-Boxes for practical applications. As a first step towards c...

It is widely recognized today that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are a family of knowledge representation languages that have gained considerable attention the last decade, mainly due to their decidability and the existence of empirically...

The Semantic Web can be viewed as largely about "Knowledge meets the Web". Thus its vision includes ontologies and rules. A key requirement for the architecture of the Semantic Web is to be able to layer "rules on top of ontologies" and "ontologies on top of rules". This has as a counterpart the definition of a mapping between Description Logics an...

EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.1.3.1 (WP2.1) This deliverable gives an overview of concepts and methods necessary for achieving scalability through modularization of ontologies. This includes partitioning algorithms for large ontolo-gies into smaller modules, distributed reasoning, e.g. distributed RDF queryi...

Fuzzy Description Logics (f-DLs) have been proposed as for- malisms capable of capturing and reasoning about imprecise and vague knowledge. The last years, research in Description Logics, and also in f- DLs, is largely focused on the development of languages where complexity of query answering is as ecient as query answering in data bases. One such...

Fuzzy Description Logics (Fuzzy DLs) and fuzzy OWL have been proposed as languages able to represent and reason about imprecise and vague knowledge. Such extensions have gained considerable atten- tion the last couple of years since on the one hand they are pivotal for applications that are inherently imprecise, like multimedia analysis and retriev...

The RuleML initiative defines a normalized markup for ex- pressing and exchange rules in the Semantic Web. However, the syntax of the language is still limited and lacks features for rep- resenting rule-based languages capable of handling uncertainty. It is desirable to have a general extension of RuleML which ac- commodates major existing language...

The semantic Web must handle information from applications that have special knowledge representation needs and that face uncertain, imprecise knowledge. More precisely, some applications deal with random information and events, others deal with imprecise and fuzzy knowledge, and still others deal with missing or distorted information - resulting i...

Fuzzy Description Logics (fuzzy DLs) have been proposed as a language to describe structured knowledge with vague concepts. A major theoretical and computational limitation so far is the inability to deal with General Concept Inclusions (GCIs), which is an important feature of classical DLs. In this paper, we address this issue and develop a calcul...

In an attempt to extend existing knowledge representation systems to deal with the imperfect nature of real world information in- volved in several applications, the AI community has devoted consider- able attention to the representation and management of uncertainty, im- precision and vague knowledge. Moreover, a lot of work has been carried out o...

Fuzzy Description Logics have been proposed in the literature as a way to represent and reason with vague and imprecise knowledge. Their decidability, the empirically tractable and ecient reasoning algorithms, that carry over to fuzzy Description Logics, have attracted the attention of many research communities and domains that deal with a wealth o...

In the current paper we investigate the role of Euclidian roles in De- scription Logics.

Uncertainty, like imprecision and vagueness, has gained considerable attention the last decade. To this extend we present a preliminary report on extending the Rule Markup Language (RuleML) with fuzzy set theory, in order to be able to represent and handle vague knowledge. We also provide semantics for the case of fuzzy FOL RuleML.

EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.5.3 (WP2.5) Keyword list: description logics, ontology language, query language, RDF, OWL DL, OWL-E In D2.5.2 "Report on Query Language Design and Standardisation", we have investigated query answering of conjunctive queries in the OWL-QL framework, including treating RDF triple...

Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Un- fortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or over- lappin...

In the Semantic Web information would be retrieved, pro- cessed, combined, shared and reused in the maximum automatic way possible. Obviously, such procedures involve a high degree of uncertainty and imprecision. For example ontology alignment or information retrieval are rarely true or false procedures but usually involve confidence degrees or pro...

The Semantic Web is about adding formal structure and explicit semantics to web content for the purpose of more efficient information management and access by both humans and computers. Through the use of machine understandable semantics, web resources become much easier and more readily accessible. Populating the Semantic Web with multimedia metad...

This essay describes fuzzy CARIN, a knowledge representation language combining fuzzy description logics with Horn rules. Fuzzy CARIN integrates the management of fuzzy logic into the non-recursive CARIN system. It provides a sound and complete algorithm for representing and reasoning about fuzzy ALCNR\mathcal{ALCNR} extended with non-recursive Ho...

Today quite a lot of multimedia systems and applications use knowledge representation formalisms to encode and reason with knowl- edge that exists within the multimedia documents. The goal of this direc- tion is to narrow the semantic gab between the content of a multimedia object, as perceived by a human being, and as "viewed" by an informa- tion...

EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.5.4 (WP2.5) Keyword list: description logics, ontology language, query language, RDF, OWL DL, OWL-E The current deliverable surveys a number of real-world use cases encountered in the course of the KnowledgeWeb project which demonstrate limitations of the Semantic Web ontology l...

The problem of computing all subclass relationships between classes and properties is one of the most important reasoning tasks for OWL ontologies. In this paper, we propose a new class classification al-gorithm mainly motivated by the previous work in [1]. We close several gaps that were left open in the original paper and provide average opti-mal...