María Laura Caliusco

Knowledge discovery through ontology matching: An approach based on an Artificial Neural Network model

With the emergence of the Semantic Web several domain ontologies were developed, which varied not only in their structure but also in the natural language used to define them. The lack of an integrated view of all web nodes and the existence of heterogeneous domain ontologies drive new challenges in the discovery of knowledge resources which are relevant to a users request. New approaches have recently appeared for developing web intelligence and helping users avoid irrelevant results on the web. However, there remains some work to be done. This work makes a contribution by presenting an ANN-based ontology matching model for knowledge source discovery on the Semantic Web. Experimental results obtained on a real case study have shown that this model provides satisfactory responses.

OntoQualitas: A framework for ontology quality assessment in information interchanges between heterogeneous systems

Abstract Nowadays, Internet technologies and standards are being systematically used by enterprises as tools to provide an infrastructure to connect people, enterprises, and applications they are using. In such complex networked enterprises, it is increasingly challenging to interchange, share, and manage internal and external digital information. In this context, to achieve interoperability between information systems is a challenging task. In order to solve the interoperability problem at semantic level, several ontology-based approaches have emerged. Although methodologies, methods, techniques, and tools to support the ontology building process were proposed, there are no mature models to measure this process, and the quality of implemented ontologies remains a major concern. This paper presents a framework, OntoQualitas, for evaluating the quality of an ontology whose purpose is the information interchange between different contexts. OntoQualitas includes previous and new measures to evaluate the ontology considering its specific purpose. Additionally, an empirical validation of OntoQualitas is presented.

Approaching the feasibility of SBVR as modeling language for ontology development: An exploratory experiment

Ontology development techniques still constitute an open research area despite its importance in semantic aware information systems. Until now, most methods have used UML in supporting ontology development process. Recent works propose the mapping of business rules expressions to ontology statements as a building technique by means of SBVR language. However, there is still no experimental research comparing such approaches. Aim of this work is to evaluate the feasibility of mapping business domain expressions to ontology statements. An exploratory experiment comparing performance of techniques based on UML and SBVR languages is presented. Comparison is rooted in the quality assessment of the ontologies developed by 10 equally sized groups randomly conformed by 30 undergraduate engineering students and applying such techniques. Developed ontologies largely outperform the minimally acceptable quality, according to the considered quality assessment framework. There is no statistical significant difference between the quality scores of the ontologies developed by means of UML and SBVR techniques, in any of the assessed quality dimensions. The feasibility of mapping business domain expressions to ontology statements is shown: ontologies developed by means of a SBVR based approach at least equate the quality of ontologies developed by using an UML based method. Results confirm previous research about the effectiveness of UML approaches for conceptualizing lightweight ontologies while stressing the potential of the SBVR language to express complex notions of a domain of interest. The potential of SBVR to OWL 2 mappings as an ontology development technique worthy of further study is highlighted.

A set of ontology design patterns for reengineering SBVR statements into OWL/SWRL ontologies

The work presents a set of ontology design patterns.Patterns provide a way to obtain an OWL/SWRL ontology from a SBVR specification.Translations from SBVR to SWRL fill the gap in the expressive power of SBVR and OWL.Patterns are readily usable for business people or software developers.Patterns are illustrated by means of an example depicting a fictitious company. The interest in the use of ontologies for creating more intelligent and effective enterprise information systems has increased considerably in recent years. The most critical aspects during the development of these systems are: (1) to identify the ontology concepts and (2) to make explicit the business rules by means of the ontology axioms.In order to address these issues, mappings of business rules expressions to ontology statements based on different languages were proposed. Despite the efforts made in this area, some work remain to be done.This work presents a set of ontology design patterns providing a way to obtain an OWL/SWRL ontology by applying metamodel transformation rules over the SBVR specification of a business domain. Patterns are rooted in the structural specification of the standards, providing a set of mappings readily usable for business people or developers concerned with the implementation of a mapping tool. Moreover, translations from SBVR to SWRL language are presented in order to fill the gap in the expressive power of SBVR and OWL. The theoretical expressions of patterns are illustrated by means of an example depicting the core structure of a fictitious company.

An approach to define semantics for BPM systems interoperability

This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise’s business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology. For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.

ANN-agent for distributed knowledge source discovery

ThispaperpresentsanArtificialNeuralNetwork-based(ANN) agent with capabilities for discovering distributed knowledge sources. This agent has the responsibility of guiding knowledge requirements towards distributed ontology domains in the SemanticWeb, indicating i.e. potentially partners for the establishment of a dynamic collaborative relationship. The agent performs its task through a neural network model. This work shows a proposed reference architecture, explains the ontology- matching model ANN-based for the agent and presents preliminary good results obtained.

Contextual ontologies for the semantic Web - an enabling technology

To realize the goals of the semantic Web, there is a need of working on approaches focused on the machine processing semantics and approaches to systematically define conceptual models about data semantics. Ontologies are a primary means to deploy the semantic Web vision, but managing the context-dependent semantics remains an open problem. In this paper we discuss the role of contexts on the semantic Web and, present a contextual ontology modeling language called C-OML.

Knowledge Source Discovery: An Experience Using Ontologies, WordNet and Artificial Neural Networks

This paper describes our continuing research on ontology-based knowledge source discovery on the Semantic Web. The research documented here is focused on discovering distributed knowledge sources from a user query using an Artificial Neural Network model. An experience using the Wordnet multilingual database for the translation of the terms extracted from the user query and for their codification is presented here. Preliminary results provide us with the conviction that combining ANN with WordNet has clearly made the system much more efficient.

Adding semantics to electronic business documents exchanged in collaborative commerce relations

In order to support the execution of collaborative business processes, trading partners have to exchange electronic business documents. Since each partner has its own systems and culture, they could use different terms and metadata structures to represent their data, even when referring to the same domain of interest. Then, an appropriate approach for defining the semantics of these documents is required to achieve semantic interoperability. To this aim, a number of approaches have been proposed based on the use of a single domain ontology. These approaches imply the imposition of a global meaning of terms, which are used to represent the entities of a domain. This goes in opposition to one of the aims of trading partners, which is to participate in collaborative business processes without losing their autonomy and privacy. In this scenario, it is necessary to define a framework for allowing trading partners to exchange information without imposing a global meaning of it. In this paper, a novel approach is proposed in order to define the semantics of the electronic business documents interchanged between trading partners in a collaborative relationship. This approach is based on the idea of making some domain features, which are generally implicit, explicit in the domain ontologies. An application example of this approach is also presented.

A Comprehensive Framework for Representing Semantics via Context and Ontology in the Collaborative Commerce Area

Nowadays, ontologies are widely adopted to represent data semantics and to characterize different kinds of information resources. However, in certain circumstances, they are not enough to efficiently support semantic interoperability due to the lack of context-dependent techniques. This paper presents a comprehensive framework for defining the semantics of the information interchanged between autonomous entities based on the use of context and ontology. To this aim, a motivating scenario that describes a collaborative relationship is analyzed. Finally, advantages and disadvantages of this framework and future trends are discussed.