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Extract-Transform-Loading (ETL) tools integrate data from source side to target in building data warehouse. However data structure and semantic heterogeneity exits widely in the enterprise information systems. On the purpose of eliminate data heterogeneity so as to construct data warehouse, this paper introduces domain ontology into ETL process of finding the data sources, defining the rules of data...
Knowledge discovery has received more and more attention from the business community for the last few years. One of the most important and challenging problems in it is the definition of discovery process model, which are well understood, efficiency, and quality of outcome. A conceptual infrastructure for knowledge discovery process is proposed with business understanding, model selection and domain...
Compare with SOAP-based service that based on interfaces access pattern, RESTful web service is HTTP-based and use resource as the operation object. On the purpose of supporting RESTful in the enterprise information application, a Resource-oriented Information Supported Framework is constructed based on ontology construction and evolution. First, the initial ontology with relational pattern is extracted...
In this paper we propose a concept of Ontological Learning Assistant (OLA)-an ontology-based KDD1 Support Environment (KDDSE) platform for carrying out knowledge discovery. The concept is based on the critical analysis of our state-of-the-art study in intelligent KDD support utilizing ontologies. We emphasize the fundamental role of knowledge transfer and domain and technology experts cooperation...
The volumes of data in information systems are growing drastically. The systems become increasingly complex in trying to handle heterogeneity of ubiquitous components, standards, data formats, etc. According to the vision of Autonomic Computing, the complexity can be handled by introducing self-manageable components able to "run themselves." Agent Technology fits this vision, whereas interoperability...
In recent years, people from academic and practice fields put more and more effort to study various stock phenomena using techniques from AI and data mining. However, the way they process data generated from phenomena has two problems, the first is that people just focus on relations among observable data, not relations among entities which are more stable than the former ones. The other problem is...
Data migration has become a priority in many industries, spawned by a variety of business needs. Most of the existing tools for Extract, Transform and Load (ETL) process of data migration are piece-meal and do not present a complete solution. Moreover, while research has focused on the problem of Schema Mapping, a key step in the ETL process, most of the current algorithms do not perform well on real-world...
In this paper we propose a way to facilitate the issue of discovering the eGovernment services that address a citizen's need. This approach is implemented in an application, which we call a semantic portal. The semantic portal is part of our SemanticGov project architecture. The portal's components and its architecture are presented and explained. The portal's conceptual modeling is based on the generic...
Compliance management (CM) is the management process that an organization implements to ensure organizational compliance with relevant requirements and expectations. Compliance auditing (CA) is a child-process of CM where compliance rules and policies are individually checked against the organization to determine the level of compliance achieved by the organization. In this paper, we arrange organizational...
Statistical graphs are ubiquitous mechanisms for data visualization such that most, if not all, enterprises communicate information through them. However, many graphs are stored as unstructured images or proprietary binary objects, making them difficult to work with beyond the reports in which they are embedded. While graphs can be mapped to more common XML representations, these lack expressive semantics...
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