Ontology matching is the process of automatically determining the semantic equivalences between the concepts of two ontologies. Most ontology matching algorithms are based on two types of strategies: terminology-based strategies, which align concepts based on their names or descriptions, and structure-based strategies, which exploit concept hierarchies to find the alignment. In many domains, there is additional information about the relationships of concepts represented in various ways, such as Bayesian networks, decision trees, and association rules. We propose to use the similarities between these relationships to find more accurate alignments. We accomplish this by defining soft constraints that prefer alignments where corresponding concepts have the same local relationships encoded as knowledge rules. We use a probabilistic framework to integrate this new knowledge-based strategy with standard terminology-based and structure-based strategies. Furthermore, our method is particularly effective in identifying correspondences between complex concepts. Our method achieves substantially better F-score than the previous state-of-the-art on three ontology matching domains.
College of Computing and Informatics, Drexel University（德雷塞尔大学计算与信息学院）
Measuring the distance between ontological elements is fundamental for ontology matching. String-based distance metrics are notorious for shallow syntactic matching. In this exploratory study, we investigate Wasserstein distance targeting continuous space that can incorporate various types of information. We use a pre-trained word embeddings system to embed ontology element labels. We examine the effectiveness of Wasserstein distance for measuring similarity between ontologies, and discovering and refining matchings between individual elements. Our experiments with the OAEI conference track an…
University of Mannheim（曼海姆大学）；University of Economics, Prague（布拉格经济大学）；INRIA（法国国家信息与自动化研究所）；LIG（格勒诺布尔信息学实验室）；University of Oxford（牛津大学）
In the field of ontology matching, the most systematic evaluation of matching systems is established by the Ontology Alignment Evaluation Initiative (OAEI), which is an annual campaign for evaluating ontology matching systems organized by different groups of researchers. In this paper, we report on the results of an intermediary OAEI campaign called OAEI 2011.5. The evaluations of this campaign are divided in five tracks. Three of these tracks are new or have been improved compared to previous OAEI campaigns. Overall, we evaluated 18 matching systems. We discuss lessons learned, in terms of sc…
LARODEC；University of Tunis（突尼斯大学）；ISG Tunis（突尼斯高等管理学院）；IRISA（IRISA研究所）；University of Carthage（迦太基大学）；IHEC Carthage（迦太基高等商业学院）
Considering the high heterogeneity of the ontologies pub-lished on the web, ontology matching is a crucial issue whose aim is to establish links between an entity of a source ontology and one or several entities from a target ontology. Perfectible similarity measures, consid-ered as sources of information, are combined to establish these links. The theory of belief functions is a powerful mathematical tool for combining such uncertain information. In this paper, we introduce a decision pro-cess based on a distance measure to identify the best possible matching entities for a given source entit…
Typically an ontology matching technique is a combination of much different type of matchers operating at various abstraction levels such as structure, semantic, syntax, instance etc. An ontology matching technique which employs matchers at all possible abstraction levels is expected to give, in general, best results in terms of precision, recall and F-measure due to improvement in matching opportunities and if we discount efficiency issues which may improve with better computing resources such as parallel processing. A gold standard ontology matching model is derived from a model classificati…
This paper discloses the potential of OWL (Web Ontology Language) ontologies for generation of rules. The main purpose of this paper is to identify new types of rules, which may be generated from OWL ontologies. Rules, generated from OWL ontologies, are necessary for the functioning of the Semantic Web Expert System. It is expected that the Semantic Web Expert System (SWES) will be able to process ontologies from the Web with the purpose to supplement or even to develop its knowledge base.
Uncertainty in Automated Ontology Matching: Lessons Learned from an Empirical Experimentation
University of Tunis El Manar（突尼斯迦太基大学）；University of Technology Sydney（悉尼科技大学）；Tallinn University of Technology（塔林理工大学）；University of Southern Denmark（南丹麦大学）
Objects or structures that are regular take uniform dimensions. Based on the concepts of regular models, our previous research work has developed a system of a regular ontology that models learning structures in a multiagent system for uniform pre-assessments in a learning environment. This regular ontology has led to the modelling of a classified rules learning algorithm that predicts the actual number of rules needed for inductive learning processes and decision making in a multiagent system. But not all processes or models are regular. Thus this paper presents a system of polynomial equatio…
LaSIGE, Faculty of Sciences of the University of Lisbon（里斯本大学科学学院LaSIGE）
Ontology Matching aims to find a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, most of the alignments produced for large ontologies are logically incoherent. It was only recently that the use of repair techniques to improve the quality of ontology alignments has been explored. In this paper we present a novel technique for detecting incoherent concepts based on ontology modularization, and a new repair algorithm that minimizes the inc…
This paper presents an idea of inductive learning use for rule generation from ontologies. The main purpose of the paper is to evaluate the possibility of inductive learning use in rule generation from ontologies and to develop the way how this can be done. Generated rules are necessary to supplement or even to develop the Semantic Web Expert System (SWES) knowledge base. The SWES emerges as the result of evolution of expert system concept toward the Web, and the SWES is based on the Semantic Web technologies. Available publications show that the problem of rule generation from ontologies base…
Banasthali University（巴纳斯达利大学）；Center for Development of Advanced Computing（先进计算发展中心）；Apaji Institute（阿帕吉学院）
Since long, corporations are looking for knowledge sources which can provide structured description of data and can focus on meaning and shared understanding. Structures which can facilitate open world assumptions and can be flexible enough to incorporate and recognize more than one name for an entity. A source whose major purpose is to facilitate human communication and interoperability. Clearly, databases fail to provide these features and ontologies have emerged as an alternative choice, but corporations working on same domain tend to make different ontologies. The problem occurs when they …
Aristotle University of Thessaloniki（塞萨洛尼基亚里士多德大学）
Semantic Web Rule Language (SWRL) combines OWL (Web Ontology Language) ontologies with Horn Logic rules of the Rule Markup Language (RuleML) family. Being supported by ontology editors, rule engines and ontology reasoners, it has become a very popular choice for developing rule-based applications on top of ontologies. However, SWRL is probably not go-ing to become a WWW Consortium standard, prohibiting industrial acceptance. On the other hand, SPIN (SPARQL Inferencing Notation) has become a de-facto industry standard to rep-resent SPARQL rules and constraints on Semantic Web models, building o…
The Alan Turing Institute（艾伦·图灵研究所）；University of Oslo（奥斯陆大学）；Medical University of Vienna（维也纳医科大学）；Miami University（迈阿密大学）
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In the paper we present an approach that combines a lexical index, a neural embedding model and locality modules to effectively divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed methods are adequate in practice and can be integrated within the workflow of state-of-the-art systems.
This paper develops the idea of membership function assignment for OWL (Web Ontology Language) ontology elements in order to subsequently generate fuzzy rules from this ontology. The task of membership function assignment for OWL ontology elements had already been partially described, but this concerned the case, when several OWL ontologies of the same domain were available, and they were merged into a single ontology. The purpose of this paper is to present the way of membership function assignment for OWL ontology elements in the case, when there is the only one available ontology. Fuzzy rul…
Narasu’s Sarathy Institute of Technology（纳拉苏萨拉蒂理工学院）
The information retrieval systems that are present nowadays are mainly based on full text matching of keywords or topic based classification. This matching of keywords often returns a large number of irrelevant information and this does not meet the users query requirement. In order to solve this problem and to enhance the search using semantic environment, a technique named ontology is implemented for the field of poultry in this paper. Ontology is an emerging technique in the current field of research in semantic environment. This paper constructs ontology using the tool named Protege versio…
City, University of London（伦敦大学城市学院）；University of Oslo（奥斯陆大学）；Medical University of Vienna（维也纳医科大学）；University of Oxford（牛津大学）；Miami University（迈阿密大学）
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed method is adequate in practice and can be integrated within the workflow of systems unable to cope with very large ontologies.
In this paper, we present MELT-ML, a machine learning extension to the Matching and EvaLuation Toolkit (MELT) which facilitates the application of supervised learning for ontology and instance matching. Our contributions are twofold: We present an open source machine learning extension to the matching toolkit as well as two supervised learning use cases demonstrating the capabilities of the new extension.
Information and knowledge are transformable into each other. Information transformation into knowledge by the example of rule generation from OWL (Web Ontology Language) ontology has been shown during the development of the SWES (Semantic Web Expert System). The SWES is expected as an expert system for searching OWL ontologies from the Web, generating rules from the found ontologies and supplementing the SWES knowledge base with these rules. The purpose of this paper is to show knowledge transformation into information by the example of ontology generation from rules.
University of Sistan and Baluchestan（锡斯坦-俾路支斯坦大学）；University of Isfahan（伊斯法罕大学）
Ontology matching finds correspondences between similar entities of different ontologies. Two ontologies may be similar in some aspects such as structure, semantic etc. Most ontology matching systems integrate multiple matchers to extract all the similarities that two ontologies may have. Thus, we face a major problem to aggregate different similarities. Some matching systems use experimental weights for aggregation of similarities among different matchers while others use machine learning approaches and optimization algorithms to find optimal weights to assign to different matchers. However, …
Recent years have witnessed the successful application of low-dimensional vector space representations of knowledge graphs to predict missing facts or find erroneous ones. However, it is not yet well-understood to what extent ontological knowledge, e.g. given as a set of (existential) rules, can be embedded in a principled way. To address this shortcoming, in this paper we introduce a general framework based on a view of relations as regions, which allows us to study the compatibility between ontological knowledge and different types of vector space embeddings. Our technical contribution is tw…
Ontologies provide a formal description of concepts and their relationships in a knowledge domain. The goal of ontology alignment is to identify semantically matching concepts and relationships across independently developed ontologies that purport to describe the same knowledge. In order to handle the widest possible class of ontologies, many alignment algorithms rely on terminological and structural meth- ods, but the often fuzzy nature of concepts complicates the matching process. However, one area that should provide clear matching solutions due to its mathematical nature, is units of meas…
Ontology merging is important, but not always effective. The main reason, why ontology merging is not effective, is that ontology merging is performed without considering goals. Goals define the way, in which ontologies to be merged more effectively. The paper illustrates ontology merging by means of rules, which are generated from these ontologies. This is necessary for further use in expert systems.
Delft University of Technology（代尔夫特理工大学）；Ferdowsi University of Mashhad（马什哈德 Ferdowsi 大学）；TNO Research Institute（TNO 研究所）
Ontology alignment is widely-used to find the correspondences between different ontologies in diverse fields.After discovering the alignments,several performance scores are available to evaluate them.The scores typically require the identified alignment and a reference containing the underlying actual correspondences of the given ontologies.The current trend in the alignment evaluation is to put forward a new score(e.g., precision, weighted precision, etc.)and to compare various alignments by juxtaposing the obtained scores. However,it is substantially provocative to select one measure among o…
Indian Institute of Information Technology Allahabad（阿拉哈巴德印度信息技术学院）
Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks, mosquitoes, triatomine bugs, blackflies, and sandflies. If these diseases are not properly treated within a reasonable time frame, the mortality rate may rise. In this work, we propose a set of ontologies that will help in the diagnosis and treatment of vector-borne diseases. For developing VBD's ontology, electronic health records taken from the Indian Health Records website, text data generated from Indian governme…
University of Valenciennes and Hainaut-Cambrésis（瓦伦谢纳与埃诺-康布雷西大学）；University of Sfax（斯法克斯大学）；University of Louisiana at Lafayette（路易斯安那大学拉斐特分校）
There is a relatively small amount of research covering urban freight movements. Most research dealing with the subject of urban mobility focuses on passenger vehicles, not commercial vehicles hauling freight. However, in many ways, urban freight transport contributes to congestion, air pollution, noise, accident and more fuel consumption which raises logistic costs, and hence the price of products. The main focus of this paper is to propose a new solution for congestion in order to improve the distribution process of goods in urban areas and optimize transportation cost, time of delivery, fue…
The Human Phenotype Ontology (HPO) is a structured repository of concepts (HPO Terms) that are associated to one or more diseases. The process of association is referred to as annotation. The relevance and the specificity of both HPO terms and annotations are evaluated by a measure defined as Information Content (IC). The analysis of annotated data is thus an important challenge for bioinformatics. There exist different approaches of analysis. From those, the use of Association Rules (AR) may provide useful knowledge, and it has been used in some applications, e.g. improving the quality of ann…
CENTRIA（里斯本新大学科学技术学院信息学系人工智能中心）；Faculdade Ciências e Tecnologias Universidade Nova de Lisboa（里斯本新大学科学技术学院）
Ontologies and rules are usually loosely coupled in knowledge representation formalisms. In fact, ontologies use open-world reasoning while the leading semantics for rules use non-monotonic, closed-world reasoning. One exception is the tightly-coupled framework of Minimal Knowledge and Negation as Failure (MKNF), which allows statements about individuals to be jointly derived via entailment from an ontology and inferences from rules. Nonetheless, the practical usefulness of MKNF has not always been clear, although recent work has formalized a general resolution-based method for querying MKNF w…
Sun Yat-sen University（中山大学）；Huazhong University of Science and Technology（华中科技大学）；Fudan University（复旦大学）；Werstern Sydney University（西悉尼大学）
Traditional inconsistency-tolerent query answering in ontology-based data access relies on selecting maximal components of an ABox/database which are consistent with the ontology. However, some rules in ontologies might be unreliable if they are extracted from ontology learning or written by unskillful knowledge engineers. In this paper we present a framework of handling inconsistent existential rules under stable model semantics, which is defined by a notion called rule repairs to select maximal components of the existential rules. Surprisingly, for R-acyclic existential rules with R-stratifi…
Ontology matching is a core task when creating interoperable and linked open datasets. In this paper, we explore a novel structure-based mapping approach which is based on knowledge graph embeddings: The ontologies to be matched are embedded, and an approach known as absolute orientation is used to align the two embedding spaces. Next to the approach, the paper presents a first, preliminary evaluation using synthetic and real-world datasets. We find in experiments with synthetic data, that the approach works very well on similarly structured graphs; it handles alignment noise better than size …
To appear in Theory and Practice of Logic Programming (TPLP), 2008. We 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 …
Efficient ontology debugging is a cornerstone for many activities in the context of the Semantic Web, especially when automatic tools produce (parts of) ontologies such as in the field of ontology matching. The best currently known interactive debugging systems rely upon some meta information in terms of fault probabilities, which can speed up the debugging procedure in the good case, but can also have negative impact on the performance in the bad case. The problem is that assessment of the meta information is only possible a-posteriori. Consequently, as long as the actual fault is unknown, th…
In the knowledge engineering community "ontology" is usually defined in the tradition of Gruber as an "explicit specification of a conceptualization". Several variations of this definition exist. In the paper we argue that (with one notable exception) these definitions are of no explanatory value, because they violate one of the basic rules for good definitions: The defining statement (the definiens) should be clearer than the term that is defined (the definiendum). In the paper we propose a different definition of "ontology" and discuss how it helps to explain various phenomena: the ability o…
Huazhong University of Technology & Science（华中科技大学）；Western Sydney University（西悉尼大学）；University of Alberta（阿尔伯塔大学）
Existential rules, also known as data dependencies in Databases, have been recently rediscovered as a promising family of languages for Ontology-based Query Answering. In this paper, we prove that disjunctive embedded dependencies exactly capture the class of recursively enumerable ontologies in Ontology-based Conjunctive Query Answering (OCQA). Our expressive completeness result does not rely on any built-in linear order on the database. To establish the expressive completeness, we introduce a novel semantic definition for OCQA ontologies. We also show that neither the class of disjunctive tu…
Vaal University of Technology（瓦尔理工大学）；North-West University（西北大学）
Electronic government (e-government) has been one of the most active areas of ontology development during the past six years. In e-government, ontologies are being used to describe and specify e-government services (e-services) because they enable easy composition, matching, mapping and merging of various e-government services. More importantly, they also facilitate the semantic integration and interoperability of e-government services. However, it is still unclear in the current literature how an existing ontology building methodology can be applied to develop semantic ontology models in a go…
Edinburgh Law School, University of Edinburgh（爱丁堡大学法学院）
Ontology is a popular method for knowledge representation in different domains, including the legal domain, and description logics (DL) is commonly used as its description language. To handle reasoning based on inconsistent DL-based legal ontologies, the current paper presents a structured argumentation framework particularly for reasoning in legal contexts on the basis of ASPIC+, and translates the legal ontology into formulas and rules of an argumentation theory. With a particular focus on the design of autonomous vehicles from the perspective of legal AI, we show that using this combined th…
The project of the Ontology Web Search Engine is presented in this paper. The main purpose of this paper is to develop such a project that can be easily implemented. Ontology Web Search Engine is software to look for and index ontologies in the Web. OWL (Web Ontology Languages) ontologies are meant, and they are necessary for the functioning of the SWES (Semantic Web Expert System). SWES is an expert system that will use found ontologies from the Web, generating rules from them, and will supplement its knowledge base with these generated rules. It is expected that the SWES will serve as a univ…
Interactive Ontology Matching with Cost-Efficient Learning
NEC Laboratories Europe（欧洲 NEC 实验室）；Springer Nature（施普林格·自然）；Zurich University of Applied Sciences（苏黎世应用科技大学）；Universidad de Castilla-La Mancha（卡斯蒂利亚-拉曼恰大学）
The covid19 pandemic is a global emergency that badly impacted the economies of various countries. Covid19 hit India when the growth rate of the country was at the lowest in the last 10 years. To semantically analyze the impact of this pandemic on the economy, it is curial to have an ontology. CIDO ontology is a well standardized ontology that is specially designed to assess the impact of coronavirus disease and utilize its results for future decision forecasting for the government, industry experts, and professionals in the field of various domains like research, medical advancement, technica…
Banasthali University（巴纳斯达利大学）；Center for Development of Advanced Computing（先进计算发展中心）
With the web getting bigger and assimilating knowledge about different concepts and domains, it is becoming very difficult for simple database driven applications to capture the data for a domain. Thus developers have come out with ontology based systems which can store large amount of information and can apply reasoning and produce timely information. Thus facilitating effective knowledge management. Though this approach has made our lives easier, but at the same time has given rise to another problem. Two different ontologies assimilating same knowledge tend to use different terms for the sa…
Center for Semantic Web Research（语义网研究中心）；University of Chile（智利大学）；TU Wien（维也纳工业大学）；University of Edinburgh（爱丁堡大学）
Many efforts have been dedicated to identifying restrictions on ontologies expressed as tuple-generating dependencies (tgds), a.k.a. existential rules, that lead to the decidability for the problem of answering ontology-mediated queries (OMQs). This has given rise to three families of formalisms: guarded, non-recursive, and sticky sets of tgds. In this work, we study the containment problem for OMQs expressed in such formalisms, which is a key ingredient for solving static analysis tasks associated with them. Our main contribution is the development of specially tailored techniques for OMQ con…
Multimedia reasoning, which is suitable for, among others, multimedia content analysis and high-level video scene interpretation, relies on the formal and comprehensive conceptualization of the represented knowledge domain. However, most multimedia ontologies are not exhaustive in terms of role definitions, and do not incorporate complex role inclusions and role interdependencies. In fact, most multimedia ontologies do not have a role box at all, and implement only a basic subset of the available logical constructors. Consequently, their application in multimedia reasoning is limited. To addre…
Traffic regulation must be respected by all vehicles, either human- or computer- driven. However, extreme traffic situations might exhibit practical cases in which a vehicle should safely and reasonably relax traffic regulation, e.g., in order not to be indefinitely blocked and to keep circulating. In this paper, we propose a high-level representation of an automated vehicle, other vehicles and their environment, which can assist drivers in taking such "illegal" but practical relaxation decisions. This high-level representation (an ontology) includes topological knowledge and inference rules, …
This paper describes the realization of the Ontology Web Search Engine. The Ontology Web Search Engine is realizable as independent project and as a part of other projects. The main purpose of this paper is to present the Ontology Web Search Engine realization details as the part of the Semantic Web Expert System and to present the results of the Ontology Web Search Engine functioning. It is expected that the Semantic Web Expert System will be able to process ontologies from the Web, generate rules from these ontologies and develop its knowledge base.
Institute for Theoretical Computer Science（理论计算机科学研究所）；Technische Universität Dresden（德累斯顿工业大学）；Department of Computer Science（计算机科学系）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）
The chase is a sound and complete algorithm for conjunctive query answering over ontologies of existential rules with equality. To enable its effective use, we can apply acyclicity notions; that is, sufficient conditions that guarantee chase termination. Unfortunately, most of these notions have only been defined for existential rule sets without equality. A proposed solution to circumvent this issue is to treat equality as an ordinary predicate with an explicit axiomatisation. We empirically show that this solution is not efficient in practice and propose an alternative approach. More precise…
In this work we propose an ontology to support automated negotiation in multiagent systems. The ontology can be connected with some domain-specific ontologies to facilitate the negotiation in different domains, such as Intelligent Transportation Systems (ITS), e-commerce, etc. The specific negotiation rules for each type of negotiation strategy can also be defined as part of the ontology, reducing the amount of knowledge hardcoded in the agents and ensuring the interoperability. The expressiveness of the ontology was proved in a multiagent architecture for the automatic traffic light setting a…
This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's knowledge. Here, we share our experience regarding the creation of 3D semantic facility model out of unorganized 3D point clouds. Thus, a knowledge-based detection approach of objects using the OWL ontology language is presented. This knowledge is used to define SWRL detection rules. In addition, the combination of 3D processing built-ins and topological Built…
The temporal phenomena have many facets that are studied by different communities. In Semantic Web, large heterogeneous data are handled and produced. These data often have informal, semi-formal or formal temporal information which must be interpreted by software agents. In this paper we present Human Time Ontology (HuTO) an RDFS ontology to annotate and represent temporal data. A major contribution of HuTO is the modeling of non-convex intervals giving the ability to write queries for this kind of interval. HuTO also incorporates normalization and reasoning rules to explicit certain informati…
Korea Advanced Institute of Science and Technology（韩国科学技术院）
Knowledge base is the way to store structured and unstructured data throughout the web. Since the size of the web is increasing rapidly, there are huge needs to structure the knowledge in a fully automated way. However fully-automated knowledge-base evolution on the Semantic Web is a major challenges, although there are many ontology evolution techniques available. Therefore learning ontology automatically can contribute to the semantic web society significantly. In this paper, we propose full-automated ontology learning algorithm to generate refined knowledge base from incomplete knowledge ba…
Contextualized Structural Self-supervised Learning for Ontology Matching
Peoples' Friendship University of Russia (RUDN University)（俄罗斯人民友谊大学（卢蒙巴大学））；Joint Institute for Nuclear Research（联合核研究所）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；University of Skövde（舍夫德大学）；University of Illinois at Chicago（伊利诺伊大学芝加哥分校）
