319,905 research outputs found

    Query Containment Using a DLR ABox

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    Query containment under constraints is the problem of determining whether the result of one query is contained in the result of another query for every database satisfying a given set of constraints. This problem is of particular importance in information integration and warehousing where, in addition to the constraints derived from the source schemas and the global schema, inter-schema constraints can be used to specify relationships between objects in different schemas. A theoretical framework for tackling this problem using the DLR logic has been established, and in this paper we show how the framework can be extended to a practical decision procedure. The proposed technique is to extend DLR with an Abox (a set of assertions about named individuals and tuples), and to transform query subsumption problems into DLR Abox satisfiability problems. We then show how such problems can be decided, via a reification transformation, using a highly optimised reasoner for the SHIQ description logic

    User Preference Web Search -- Experiments with a System Connecting Web and User

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    We present models, methods, implementations and experiments with a system enabling personalized web search for many users with different preferences. The system consists of a web information extraction part, a text search engine, a middleware supporting top-k answers and a user interface for querying and evaluation of search results. We integrate several tools (implementing our models and methods) into one framework connecting user with the web. The model represents user preferences with fuzzy sets and fuzzy logic, here understood as a scoring describing user satisfaction. This model can be acquired with explicit or implicit methods. Model-theoretic semantics is based on fuzzy description logic f-EL. User preference learning is based on our model of fuzzy inductive logic programming. Our system works both for English and Slovak resources. The primary application domain are job offers and job search, however we show extension to mutual investment funds search and a possibility of extension into other application domains. Our top-k search is optimized with own heuristics and repository with special indexes. Our model was experimentally implemented, the integration was tested and is web accessible. We focus on experiments with several users and measure their satisfaction according to correlation coefficients

    Ontology-based patterns for the integration of business processes and enterprise application architectures

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    Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

    Semantic validation in spatio-temporal schema integration

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    This thesis proposes to address the well-know database integration problem with a new method that combines functionality from database conceptual modeling techniques with functionality from logic-based reasoners. We elaborate on a hybrid - modeling+validation - integration approach for spatio-temporal information integration on the schema level. The modeling part of our methodology is supported by the spatio-temporal conceptual model MADS, whereas the validation part of the integration process is delegated to the description logics validation services. We therefore adhere to the principle that, rather than extending either formalism to try to cover all desirable functionality, a hybrid system, where the database component and the logic component would cooperate, each one performing the tasks for which it is best suited, is a viable solution for semantically rich information management. First, we develop a MADS-based flexible integration approach where the integrated schema designer has several viable ways to construct a final integrated schema. For different related schema elements we provide the designer with four general policies and with a set of structural solutions or structural patterns within each policy. To always guarantee an integrated solution, we provide for a preservation policy with multi-representation structural pattern. To state the inter-schema mappings, we elaborate on a correspondence language with explicit spatial and temporal operators. Thus, our correspondence language has three facets: structural, spatial, and temporal, allowing to relate the thematic representation as well as the spatial and temporal features. With the inter-schema mappings, the designer can state correspondences between related populations, and define the conditions that rule the matching at the instance level. These matching rules can then be used in query rewriting procedures or to match the instances within the data integration process. We associate a set of putative structural patterns to each type of population correspondence, providing a designer with a patterns' selection for flexible integrated schema construction. Second, we enhance our integration method by employing validation services of the description logic formalism. It is not guaranteed that the designer can state all the inter-schema mappings manually, and that they are all correct. We add the validation phase to ensure validity and completeness of the inter-schema mappings set. Inter-schema mappings cannot be validated autonomously, i.e., they are validated against the data model and the schemas they link. Thus, to implement our validation approach, we translate the data model, the source schemas and the inter-schema mappings into a description logic formalism, preserving the spatial and temporal semantics of the MADS data model. Thus, our modeling approach in description logic insures that the model designer will correctly define spatial and temporal schema elements and inter-schema mappings. The added value of the complete translation (i.e., including the data model and the source schemas) is that we validate not only the inter-schema mappings, but also the compliance of the source schemas to the data model, and infer implicit relationships within them. As the result of the validation procedure, the schema designer obtains the complete and valid set of inter-schema mappings and a set of valid (flexible) schematic patterns to apply to construct an integrated schema that meets application requirements. To further our work, we model a framework in which a schema designer is able to follow our integration method and realize the schema integration task in an assisted way. We design two models, UML and SEAM models, of a system that provides for integration functionalities. The models describe a framework where several tools are employed together, each involved in the service it is best suited for. We define the functionalities and the cooperation between the composing elements of the framework and detail the logics of the integration process in an UML activity diagram and in a SEAM operation model

    A multi-INT semantic reasoning framework for intelligence analysis support

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    Lockheed Martin Corp. has funded research to generate a framework and methodology for developing semantic reasoning applications to support the discipline oflntelligence Analysis. This chapter outlines that framework, discusses how it may be used to advance the information sharing and integrated analytic needs of the Intelligence Community, and suggests a system I software architecture for such applications

    Ontology-based modelling of architectural styles

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    The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework. Architectural styles are often neglected in software architectures. We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. We introduce a framework for style definition and style combination. The application of the ontological framework in the form of an integration into existing architectural description notations is illustrated

    Semantic model-driven development of service-centric software architectures

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    Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

    Ontology-Based Data Access and Integration

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    An ontology-based data integration (OBDI) system is an information management system consisting of three components: an ontology, a set of data sources, and the mapping between the two. The ontology is a conceptual, formal description of the domain of interest to a given organization (or a community of users), expressed in terms of relevant concepts, attributes of concepts, relationships between concepts, and logical assertions characterizing the domain knowledge. The data sources are the repositories accessible by the organization where data concerning the domain are stored. In the general case, such repositories are numerous, heterogeneous, each one managed and maintained independently from the others. The mapping is a precise specification of the correspondence between the data contained in the data sources and the elements of the ontology. The main purpose of an OBDI system is to allow information consumers to query the data using the elements in the ontology as predicates. In the special case where the organization manages a single data source, the term ontology-based data access (ODBA) system is used
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