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Title: Knowledge management and Discovery for advanced Enterprise Knowledge Engineering
Authors: Novi, Daniele
Persiano, Giuseppe
Gaeta, Matteo
Keywords: Knowledge extraction;Ontology extraction;Ontology;OWL;Fuzzy relational concept analysis;Fuzzy formal concept analysis;Semantic web;Best practice;Information retrieval;Automotive
Issue Date: 2-May-2014
Publisher: Universita degli studi di Salerno
Abstract: The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. The most innovative approaches which were investigated for the "Enterprise Knowledge Engineering" are listed below. In detail, the problems analyzed are those relating to architectural aspects and the integration of Legacy Systems (or not). The contribution of research that is intended to give, consists in the identification and definition of a uniform and general model, a "Knowledge Enterprise Model", the original model with respect to the canonical approaches of enterprise architecture (for example with respect to the Object Management - OMG - standard). The introduction of the tools and principles of Enterprise 2.0 in the company have been investigated and, simultaneously, Semantic Enterprise based appropriate solutions have been defined to the problem of fragmentation of information and improvement of the process of knowledge discovery and functional knowledge sharing. All studies and analysis are finalized and validated by defining a methodology and related software tools to support, for the improvement of processes related to the life cycles of best practices across the enterprise. Collaborative tools, knowledge modeling, algorithms, knowledge discovery and extraction are applied synergistically to support these processes. [edited by author]
Description: 2012 - 2013
Appears in Collections:Informatica

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