Search

The exponential growth of data has made ontology modeling an up-and-coming research area for knowledge representation. One of the domains of interest is represented by Cultural Heritage, in which modeling of environments, such as archaeological parks, could lead to their protection and enhancement. In this scenario, the valuable dataset on the Naples Urban Archaeological Park (PAUN) is of particular interest. Due to its peculiarity, the database could benefit from innovative techniques for retrieving the information, representing a large part of the information contained within the DatabencArt platform, which collects data on Campania's cultural heritage. This paper aims to introduce an ontology-based approach to improve data retrieval, which could help expert users in the field (archaeologists, art historians, geologists, etc.). Scholars need to be able to easily compare the information. To this end, a semantic search is able to transform a vast amount of data into linked concepts. We mapped all concepts according to the ArCo ontology and equipped the DatabencArt platform with a semantic query layer, making the information accessible through ArCo ontology's properties. To evaluate the proposed approach, we designed an experimental campaign involving expert users to assess the results obtained in the system's queries through Sparql queries. The obtained results are promising. [ABSTRACT FROM AUTHOR]

Nowadays, none can expect that knowledge about some part of reality will not change. Consequently, a representation of such evolving knowledge (for example, ontologies) also changes. Such changes entail that applications incorporating such knowledge may become compromised and yield wrong results. An example of such an application is ontology alignment which can be informally described as a set of connections between two ontologies. Those connections mark elements from two ontologies that relate to the same parts of reality. In changing one of the corresponding ontologies, such connections may become invalid. One may designate the ontology alignment once again from scratch for altered ontologies. However, such an approach is time and resource-consuming. The paper comprehensively presents our ontology evolution and alignment maintenance framework. It can be used to preserve the validity of ontology alignment using only the analysis of changes introduced to maintained ontologies. The precise definition of ontologies is provided, along with a definition of the ontology change log. A set of algorithms that allow revalidating ontology alignments have been built based on such elements. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of ontology-based knowledge management on improving tax accounting procedures and reducing tax risks, specifically focusing on the income tax system in a developing country. To achieve this objective, a mixed methodology approach was adopted, combining quantitative and qualitative data collection and analysis methods. The data were gathered through document analysis, interviews, and questionnaires administered to stakeholders in the Egyptian Income Tax Authority. The findings of this study hold significance for both academic researchers and accounting practitioners. The results demonstrate numerous advantages associated with the utilization of ontology in tax management. It has the potential to reduce costs in tax advisory services, minimize errors in tax calculations, and enhance tax revenue generation by promoting transparency and accountability. The empirical analysis further confirms a positive correlation between ontology-based knowledge management and improved accountability procedures, as well as a positive correlation with the reduction of tax risks. These statistically significant relationships (r = 0.85, p < 0.01 and r = 0.79, p < 0.01, respectively) provide empirical evidence of the actual effects of implementing ontology-based knowledge management in improving tax accounting procedures and mitigating tax risks. [ABSTRACT FROM AUTHOR]

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Designing Product-Service Systems (PSS) is associated with multiple problems and challenges, usually derived from its multidisciplinarity and partially intangible nature. One particular issue is the high likelihood of ignoring the creation of relevant information regarding one or more PSS elements during the early design phases. Proceeding to later stages (e.g., detailed design) without generating the required information regarding all PSS elements and their relationships may lead to rework and lack of integration. Dealing with this problem requires adequate planning and evaluation of the artifacts (such as documents and models) created in the initial design phases. As a fundamental theoretical basis to support the creation of solutions that may help project managers dealing with this challenge, this paper presents a concept map to structure the concepts that compose artifacts resulting from the initial stages of PSS design and how those concepts interrelate. This concept map aims to structure which classes of information should be defined in the early phases of the design process before proceeding to a detailed design. The concept map was created by extracting concepts and relationships proposed in classifications, taxonomies, ontologies, meta-models, and concept maps in the PSS and servitization fields. Those documents were identified through a comprehensive systematic literature review. The resulting concept map was verified for completeness against formal documentation of two retrospective PSS design projects. The final proposed concept map is composed of 143 concepts interconnected through 278 relationships. In its current format, the concept map may be used as a checklist to support project managers in planning and evaluating early phases of PSS design based on information completeness. Researchers may also employ it to deploy ontologies, approach further knowledge and information-related challenges in PSS design, or structure PSS-related model-based systems engineering approaches. In future research, this concept map shall be deployed in a meta-model based on artifacts commonly used in PSS design, structuring a computational tool to allow and support practical application on planning and evaluating PSS design projects. [ABSTRACT FROM AUTHOR]

To achieve efficient development of high-quality product, manufacturing constraints must be fully taken into account at the early design stage. However, designers lack in-depth knowledge of manufacturing and production. Many time-consuming iterations of design changes are required between designers and manufacturing engineers. In order to minimize this knowledge gap, this paper presents an ontology-based product design framework for manufacturability verification and knowledge reuse to support the sharing and reuse of design and manufacturing knowledge. It aims at providing advices and feedback of restraints of manufacturing processes to the designers during the design process. The proposed framework consists of three major layers which include a foundation layer, a domain layer, and an instance layer. We use the Web Ontology Language (OWL), a standard of ontology representation language, to formalize the foundation layer. It contains the core product model and the standard ISO 10303 AP224 application protocol. The domain layer comprises extensional concepts and relationships for design and manufacturing integration and a rule base for manufacturability verification, which is represented in Semantic Web Rule Language (SWRL). In the instance layer, an inference engine is developed based on ontology and rule inference. It provides recommendations of manufacturability. Two case studies are provided as application examples to demonstrate the effectiveness of the framework. [ABSTRACT FROM AUTHOR]

Corporate memory (CM) is the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization. In the current market, the rapidly increasing volume of unstructured documents in the enterprises has brought the challenge of building an autonomic framework to acquire, represent, learn and maintain CM, and efficiently reason from it to aid in knowledge discovery and reuse. The concept of semantic web is being introduced in the enterprises to structure information in a machine readable way and enhance the understandability of the disparate information. Due to the continual popularity of the semantic web, this paper develops a framework for CM management on the semantic web. The proposed approach gleans information from the documents, converts into a semantic web resource using resource description framework (RDF) and RDF Schema and then identifies relations among them using latent semantic analysis technique. The efficacy of the proposed approach is demonstrated through empirical experiments conducted on two case studies. [ABSTRACT FROM AUTHOR]

Life cycle engineering design (LCED) is the key and comprehensive technology to realize manufacturing industries’ sustainable development. Its main objective is to support design teams to create products considering the entire product life-cycle from conception through manufacturing and assembly to disassembly, recycling, disposal, and lifecycle assessment. So LCED should be collaboratively implemented among the different departments. This paper puts forward knowledge management architecture of LCED based ontologies and multi-agent system. The definition of the domain-specific ontology, the multi-agent architecture are described. Based on the two concepts, this paper discusses the detailed construction of CAD agents, LCED evaluation agents and knowledge maintenance agents and the system implementation. It can fulfill the concurrent collaborative developing of a product under distributed environments and also meet the requirement of knowledge sharing, interoperability, reusing among the whole lifecycle of product. [ABSTRACT FROM AUTHOR]

The utilization of ontologies in knowledge management has become very well accepted in many approaches for instance database, semantics, agent, natural language processing, etc. Artificial intelligent researchers have originally applied the word 'ontology' from Philosophy fields which means 'being existence', then the word spread in many scientific domain and ontologies are now used in several developments. The purpose of this research is to present the simple methodologies and methods used to build/adapt/integrate ontologies from the system requirement or by reusing and re-engineering other ontologies; also a process of merging approach will be addressed. The normal ontology engineering will not be suitable for non-expert user; and there are some tools for helping the user to accomplish the ontology engineering task, however, it is not that simple. This paper mentioned the observation and figure out the practical methodology for non-expert user to learn and create simple ontology with little background of them. This paper mentioned the ontology and ontology engineering revisits. Also the main section in this paper mentioned the scenario walkthrough about reality of how non-expert user creates the simple ontology by using suggested and existing methodologies. The last section is recommendation and suggestion from the research experimental which explain the proper ontology developing methodology for non-expert user. [ABSTRACT FROM AUTHOR]

This paper demonstrates the development of ontology for satellite databases. First, I create a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD for short), called the UCS Satellite Ontology (or UCSSO). Second, in developing UCSSO I show that The Space Situational Awareness Ontology (SSAO) (Rovetto & Kelso 2016)--an existing space domain reference ontology--and related ontology work by the author (Rovetto 2015, 2016) can be used either (i) with a database-specific local ontology such as UCSSO, or (ii) in its stead. In case (i), local ontologies such as UCSSO can reuse SSAO terms, perform term mappings, or extend it. In case (ii), the author's orbital space ontology work, such as the SSAO, is usable by the UCSSD and organizations with other space object catalogs, as a reference ontology suite providing a common semantically-rich domain model. The SSAO, UCSSO, and the broader Orbital Space Environment Domain Ontology project is online at and GitHub. This ontology effort aims, in part, to provide accurate formal representations of the domain for various applications. Ontology engineering has the potential to facilitate the sharing and integration of satellite data from federated databases and sensors for safer spaceflight. [ABSTRACT FROM AUTHOR]

Knowledge mobilisation is a transition from the prevailing knowledge management technology that has been widely used in industry for the last 20 years to a new methodology and some innovative methods for knowledge representation, formation and development and for knowledge retrieval and distribution. Knowledge mobilisation aims at coming to terms with some of the problems of knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the knowledge mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone. [ABSTRACT FROM AUTHOR]

In the body shop of an automobile assembly plant, having access to correct and timely information is very important in solving problems encountered in the assembly process. The Variation Reduction Adviser (VRA) system used within General Motors (GM) is a database containing problems encountered in this process and their possible solutions. The VRA acts as an electronic logbook that shares information across shifts within a plant as well as across multiple plants. The VRA also serves as a problem-solving tool by which solutions to problems encountered may be retrieved and reused. To function effectively as a problem-solving tool, it is important that relevant information is quickly retrieved from the VRA database. Traditionally, keyword-based retrieval strategies have been used. In these approaches, the user types in a list of words or phrases and those records in the database that contain those words or phrases exactly as typed are retrieved. The problem with this approach is that records containing words or phrases that are semantically related to the ones typed in but not exactly the same are not retrieved. For instance, if the user types “left-hand side,” the traditional keyword search will not find records that contain the abbreviation “LHS.” This paper describes a search mechanism based on a thesaurus (a simple version of an ontology) that overcomes this problem. It describes the standard criteria to measure the effectiveness of a search, defines a new criterion, and shows that in terms of these criteria, the ontology-guided approach gives better search results than the exact match mechanism. The results are shown in the context of real searches during the use of the VRA in a GM assembly plant. [ABSTRACT FROM AUTHOR]

The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human- Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology. [ABSTRACT FROM AUTHOR]

The effective generation, sharing and re-use of innovation knowledge play an increasingly crucial role in the competitiveness of industrial enterprises allowing the companies to offer new solutions based on rapidly exploited innovations. As the innovation knowledge is by its nature very unstructured and manifold in its definition, solutions for effective exchange and sharing of such knowledge within collaboration networks of extended enterprises are still missing. This paper presents a set of new methods and IT tools to support efficient and smooth exchange of innovation knowledge in extended and networked enterprises. The methods and tools are based on so-called hybrid approach in definition of ontologies needed as a basis for knowledge sharing within a network of companies. The developed tools enable efficient set-up, harmonisation and maintenance of generic, shared ontologies. The solutions are tested within a large manufacturing enterprise involving several subsidiaries. [ABSTRACT FROM AUTHOR]

A video retrieval system user hopes to find relevant information when the proposed queries are ambiguous. The retrieval process based on detecting concepts remains ineffective in such a situation. Potential relationships between concepts have been shown as a valuable knowledge resource that can enhance the retrieval effectiveness, even for ambiguous queries. Recent researches in multimedia retrieval have focused on ontology modeling as a common framework to manage knowledge. Handling these ontologies has to cope with issues related to generic knowledge management and processing scalability. Considering these issues, we suggest a context-based fuzzy ontology framework for video content analysis and indexing. In this paper, we focused on the way in which we modeled our fuzzy ontology: First, we populate automatically the generated ontology by gathering various available video annotation datasets. Then, the ontology content was used to infer enhanced video semantic interpretation. Finally, considering user feedback, the content of the ontology was improved. Experimental results showed that our approach achieves the goal of scalability while at the same time allowing better video content semantic interpretation. [ABSTRACT FROM AUTHOR]

Three-dimensional content offers a powerful medium enabling rich, interactive visualization in virtual and augmented reality systems, which are increasingly used in a variety of application domains, such as education, training, tourism and cultural heritage. The creation of interactive 3D presentations is typically a complex process covering diverse aspects of the content such as geometry, structure, space, appearance, animation and behavior. Recent trends in the development of the semantic web provide new opportunities for simplifying 3D content creation, which may be performed at different levels of abstraction and may encompass the inference of hidden knowledge, which may influence the created content. However, the available approaches to 3D content creation do not enable conceptual knowledge-based modeling of 3D content. The main contribution of this paper is an approach to semantic creation of 3D content. The proposed solution leverages the semantic web techniques to enable conceptual, knowledge-driven content creation. The proposed approach has been implemented and evaluated. It has been shown that the approach can significantly simplify modeling of advanced 3D content presentations in comparison with the available approaches. [ABSTRACT FROM AUTHOR]

A business process is a sequence of activities that aims at creating products or services, granting value to the customer, and is generally represented by a business process model. Business process models play an important role in bridging the gap between the business domain and the information technology, increasing the weight of business modeling as first step of software development. However, the traditional way of representing a process is not suitable for the so-called Knowledge-Intensive Processes (KIP). This type of process comprises sequences of activities based on intensive acquisition, sharing, storage and (re)use of knowledge, so that the amount of value added to the organization depends on the actor knowledge. Current research in the literature points to the lack of approaches to make this kind of process explicit and strategies for handling information that is necessary for their understanding and support. The goal of this paper is to present KIPO-a knowledge-intensive process ontology, which encompasses a clear and semantically rich definition of KIPs, and to discuss the results of a case study to evaluate KIPO with regard to its applicability and capability of making all relevant knowledge embedded in a KIP explicit. [ABSTRACT FROM AUTHOR]

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing a colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as the exploitation of lexical databases for explicit semantic-based query expansion. [ABSTRACT FROM AUTHOR]

Large-scaled software development inevitably involves a group of stakeholders, each of whom may express their requirements differently in their own terminology and representation depending on their perspectives or perceptions of their shared problems. In view of that, the heterogeneity must be well handled and resolved in tracing and managing changes of such requirements. This paper presents our multiperspective requirements traceability (MUPRET) framework which deploys ontology as a knowledge management mechanism to intervene mutual 'understanding' without restricting the freedom in expressing requirements differently. Ontology matching is applied as a reasoning mechanism in automatically generating traceability relationships. The relationships are identified by deriving semantic analogy of ontology concepts representing requirements elements. The precision and recall of traceability relationships generated by the framework are verified by comparing with a set of traceability relationships manually identified by users as a proof-of-concept of this framework. [ABSTRACT FROM AUTHOR]

This paper details an integrated methodology to optimise knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses ontologies as a central modelling strategy for the capture of knowledge from legacy documents via automated means, or directly in systems interfacing with knowledge workers, via user-defined, web-based forms. The domain ontologies used for knowledge capture also guide the retrieval of the knowledge extracted from the data using a semantic search system that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale. [ABSTRACT FROM AUTHOR]

Advances in information technology and knowledge management change the way that e-negotiations, which constitute an important aspect of worldwide e-trading, can be structured and represented. In this paper, a novel approach that focuses on knowledge modeling, formalization, representation and management in the domain of e-negotiation is described. The proposed approach exploits Ontologies, Service Oriented Architectures, Semantic Web Services, software agent platforms, and Knowledge-Bases to construct a framework that favors dynamically adapted negotiation protocols, negotiation process visualization and management, modeling and preference elicitation of the negotiated object and automatic deployment of negotiation interfaces. Negotiation process, protocol and strategy are examined, and a hybrid approach that integrates rules and workflow diagrams to describe and represent them is introduced. [ABSTRACT FROM AUTHOR]

This paper describes a preliminary attempt at using the Semantic Web paradigm, particularly the Web Ontology Language (OWL), for domain-specific engineering design knowledge representation in a multi-agent distributed design environment. Ontology-based modeling to the engineering design knowledge on the Semantic Web is proposed as a prelude to the meaningful agent communication and knowledge reuse for collaborative work among multidisciplinary organizations. Formal knowledge representation in OWL format extends traditional product modeling with capabilities of knowledge sharing and distributed problem solving, and is used as a content language within the FIPA-ACL (Agent Communication Language) messages in the proposed multi-agent system architecture. As an illustration, engineering design knowledge of automatic assembly systems for manufacturing electronic connectors, which contain a group of electro-mechanical components, is represented in OWL format, with its inherent structure-function-process relationships defined explicitly and formally, to facilitate semantic access and retrieval of electro-mechanical component information across different disciplines. The proposed approach is viewed as a promising knowledge-management method that facilitates the implementation of computer supported cooperative work (CSCW) in design of Semantic Web applications. [ABSTRACT FROM AUTHOR]

Knowledge management research focuses on concepts, methods, and tools supporting the management of human knowledge. The main objective of this paper is to survey basic concepts that have been used in computer science for the representation of knowledge and summarize some of their advantages and drawbacks. A secondary objective is to relate these techniques to information science theory and practice. The survey classifies the concepts used for knowledge representation into four broad ontological categories. Static ontologies describe static aspects of the world, i.e., what things exist, their attributes and relationships. A dynamic ontology, on the other hand, describes the changing aspects of the world in terms of states, state transitions and processes. Intentional ontologies encompass the world of things agents believe in, want, prove or disprove, and argue about. Finally, social ontologies cover social settings – agents, positions, roles, authority, permanent organizational structures or shifting networks of alliances and interdependencies. [ABSTRACT FROM AUTHOR]

Recently, smart glasses have been applied in the field of maintenance, with which a worker goes well during work by contacting a support operator from a remote location. The worker, however, cannot go well if the support operator is not there. To solve the issues, this paper discusses how a work system should be developed by integrating smart glasses with a question-answering module. We design the work knowledge acquired from skilled people and manuals as a workflow for when type of question, rule base for how, goal tree for why, domain ontologies, and its RDF data for what. Workers can receive answers from the question-answering module incorporated with multiple knowledge bases for four types of question. The authors conducted a demonstration experiment and found that workers could perform the work more autonomously by importing the system. [ABSTRACT FROM AUTHOR]

Ontologies are recognised as important tools, not only for effective and efficient information sharing, but also for information extraction and text mining. In the biomedical domain, the need for a common ontology for information sharing has long been recognised, and several ontologies are now widely used. However, there is confusion among researchers concerning the type of ontology that is needed for text mining , and how it can be used for effective knowledge management, sharing, and integration in biomedicine. We argue that there are several different ways to define an ontology and that, while the logical view is popular for some applications, it may be neither possible nor necessary for text mining. We propose a text-centered approach for knowledge sharing, as an alternative to formal ontologies. We argue that a thesaurus (i.e. an organised collection of terms enriched with relations) is more useful for text mining applications than formal ontologies. [ABSTRACT FROM AUTHOR]

The global economy faces different types of intercultural conflicts. In the meanwhile, there is a dramatic change in the labor market. These processes are turbulent and have significant impact on the societies. The integration of the immigrants as a phenomenon constitutes a burden and an opportunity at the same time. The context of the synergic collaboration can be consciously determined with the proper application of knowledge management. The aim of the current research is to draw an applicable framework for enhancing the integration of the immigrants and to provide an opportunity to grow the economy and to solidify the interactions within the society by maintaining the social control in the cross-cultural cooperation. [ABSTRACT FROM AUTHOR]

Language can be a tool to marginalize certain groups due to the fact that it may reflect a negative mentality caused by mental barriers or historical delays. In order to prevent misuse of language, several agents have carried out campaigns against discriminatory language, criticizing the use of some terms and phrases. However, there is an important gap in detecting discriminatory text in documents because language is very flexible and, usually, contains hidden features or relations. Furthermore, the adaptation of approaches and methodologies proposed in the literature for text analysis is complex due to the fact that these proposals are too rigid to be adapted to different purposes for which they were intended. The main novelty of the methodology is the use of ontologies to implement the rules that are used by the developed text analyzer, providing a great flexibility for the development of text analyzers and exploiting the ability to infer knowledge of the ontologies. A set of rules for detecting discriminatory language relevant to gender and people with disabilities is also presented in order to show how to extend the functionality of the text analyzer to different discriminatory text areas. [ABSTRACT FROM AUTHOR]

Ontology is one of the key components in semantic webs. It contains the core knowledge for an effective search. However, building ontology requires the carefully-collected knowledge which is very domain-sensitive. In this work, we present the practice of ontology construction for a case study of health tourism in Thailand. The whole process follows the METHONTOLOGY approach, which consists of phases: information gathering, corpus study, ontology engineering, evaluation, publishing, and the application construction. Different sources of data such as structure web documents like HTML and other documents are acquired in the information gathering process. The tourism corpora from various tourism texts and standards are explored. The ontology is evaluated in two aspects: automatic reasoning using Pellet, and RacerPro, and the questionnaires, used to evaluate by experts of the domains: tourism domain experts and ontology experts. The ontology usability is demonstrated via the semantic web application and via example axioms. The developed ontology is actually the first health tourism ontology in Thailand with the published application. [ABSTRACT FROM AUTHOR]

More people than ever before have access to information with the World Wide Web; information volume and number of users both continue to expand. Traditional search methods based on keywords are not effective, resulting in large lists of documents, many of which unrelated to users' needs. One way to improve information retrieval is to associate meaning to users' queries by using ontologies, knowledge bases that encode a set of concepts about one domain and their relationships. Encoding a knowledge base using one single ontology is usual, but a document collection can deal with different domains, each organized into an ontology. This work presents a novel way to represent and organize knowledge, from distinct domains, using multiple ontologies that can be related. The model allows the ontologies, as well as the relationships between concepts from distinct ontologies, to be represented independently. Additionally, fuzzy set theory techniques are employed to deal with knowledge subjectivity and uncertainty. This approach to organize knowledge and an associated query expansion method are integrated into a fuzzy model for information retrieval based on multi-related ontologies. The performance of a search engine using this model is compared with another fuzzy-based approach for information retrieval, and with the Apache Lucene search engine. Experimental results show that this model improves precision and recall measures. [ABSTRACT FROM AUTHOR]

Nowadays many techniques and tools are available for addressing the ontology matching problem, however, the complex nature of this problem causes existing solutions to be unsatisfactory. This work aims to shed some light on a more flexible way of matching ontologies. Ontology meta-matching, which is a set of techniques to configure optimum ontology matching functions. In this sense, we propose two approaches to automatically solve the ontology meta-matching problem. The first one is called maximum similarity measure, which is based on a greedy strategy to compute efficiently the parameters which configure a composite matching algorithm. The second approach is called genetics for ontology alignments and is based on a genetic algorithm which scales better for a large number of atomic matching algorithms in the composite algorithm and is able to optimize the results of the matching process. [ABSTRACT FROM AUTHOR]

One of the most important research subjects germane to knowledge management in collaborative manufacturing is the integration of heterogeneous product knowledge distributed among different collaborative enterprises. To deal with the problem of optimization of knowledge integration in collaborative manufacturing, an ontology-based framework of knowledge integration is presented to transform the problem of knowledge integration into a problem of ontology integration. First of all, a collaborative business process for collaborative enterprises is described, and then an ontology-based framework of knowledge integration is established. Under the condition of analyzing the structure of knowledge ontology, an ontology schema of knowledge concept is discussed. Aiming at the ontology schema, a method of ontology integration based on ontology similarity is improved. The method is composed of ontology mapping and ontology merging, which is based on calculated result of ontology similarity between local ontology and global ontology. Finally, the implementation of the framework of knowledge integration is described, and the application results meet the requirement of the knowledge integration to ensure that validity of the ontology integration method was proved. [ABSTRACT FROM AUTHOR]

A novel idea and architecture of a group decision support system for reaching consensus in a group of individuals (agents) is proposed. The core of the system is the preferences modeling and consensus assessment module, which is based on fuzzy logic. However, the focus is on providing the members of the group with an information- and knowledge-rich environment, and tools to make an effective and efficient use of such an environment. This should help the agent gain proper opinions about the issues and opinions and/or attitudes of other agents, articulate proper testimonies, actively contribute to the discussion, and finally make sound and informed decisions that can help constructively run the consensus reaching process. For this purpose modern Web-based technologies are employed and tightly integrated with the core of the system. [ABSTRACT FROM AUTHOR]

Ontologies are an important component in many areas, such as knowledge management and organization, electronic commerce and information retrieval and extraction. Several methodologies for ontology building have been proposed. In this article, we provide an overview of ontology building. We start by characterizing the ontology building process and its life cycle. We present the most representative methodologies for building ontologies from scratch, and the proposed techniques, guidelines and methods to help in the construction task. We analyze and compare these methodologies. We describe current research issues in ontology reuse. Finally, we discuss the current trends in ontology building and its future challenges, namely, the new issues for building ontologies for the Semantic Web. [ABSTRACT FROM AUTHOR]