Modeling of Knowledge with Imprecision in Linked Data Environment

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The web becomes an enormous repository of data and information. Its constant growth creates a lot of opportunities as well as challenges for the users: How to embrace large amounts of data? How to find new pieces of information? How to deal with imprecision and missing data? How to convert data into information and then into knowledge? Fortunately, we are at the onset of significant and far-reaching changes in the way data are represented and stored on the web. One of the most fundamental aspects of the Semantic Web – Resource Description Framework – is generating a lot of attention. The application of Resource Description Framework induces a truly distributed and highly interconnected network of data. This creates an environment suitable for addressing the questions stated above.   The proposed research project puts a special emphasis on processes of constructing, updating and utilizing knowledge models built based on data and information obtained on the web. A key innovation of this project is a fusion of Computational Intelligence techniques with web technologies to fully explore data, including temporal data, and to take advantage of Resource Description Framework’s intrinsic interconnectivity. These activities will lead to establishing coherent rudiments of knowledge creation processes and systems. In a nutshell, the proposed methodology focuses on forming knowledge models using 1) a hierarchical clustering of Resource Description Framework data; 2) an automatic generalization of the constructed clusters; maintaining the models with incremental updates using aggregation and data assimilation techniques that take into account imprecision and confidence levels in different pieces of data, as well as temporal information about data; and visual and query-based exploration of knowledge models leading to multi-facet processing of data and knowledge.  The proposed project exhibits a direct and essential impact on the current and future research in the area of intelligent web systems. It is expected that the project will lead to significant contributions in methodologies focused on building new generation of systems that support the users in their activities related to collecting data from the web, and processing it towards creation of knowledge. This could lead to personal knowledge repositories that will help users with their activities of utilizing information available on the web.   The project would provide not only immediate results in the form of creation of intellectual property (new technologies, patents), but also in preparation of future generation of engineers and researchers equipped with highly competitive skills. These aspects of the project would support Canada’s pursuit to become one of the top technologically advanced countries. The project will contribute to the generation of employment and development of advanced technologies.