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There are some independent cyber security knowledge bases for different aspect now. In the internet, there is also much cyber security related content which exists in the form of text. Fusion of these cyber security related information can be a meaningful work. In this paper, we propose a framework to integrate existing cyber security knowledge base and extract cyber security related information from...
The increasing complexity of IT environments dictates the usage of intelligent automation driven by cognitive technologies, aiming at providing higher quality and more complex services. Inspired by cognitive computing, an integrated framework is proposed for a problem resolution. In order to improve the efficiency of the problem resolution process, it is crucial to formalize problem records and discover...
With the fast growth of World Wide Web 2.0, a great number of opinions about a variety of products have been published in blogs, forums, and social networks. Opinion mining tools are needed to enable users to efficiently process a large number of reviews found online, in order to determine the underlying opinions. This paper presents a new methodology for semantic modelling of the domain knowledge...
This article deals with the concept development methodological principles of conceptualization of the economic systems using ontological modelling. Proposed approach enables to build ontology of any economic system on micro- and macro levels, to form the set of problem situations and set of ways of their overcoming which are the basis for designing the knowledge base of the intelligence system.
This paper investigates the independence relation of concepts and its application to conceptual modeling which is important for knowledge engineering and software engineering of today. Four possible (collectively exhaustive and mutually exclusive) basic relations of two concepts are given and analyzed, whereby the notion of independence relation is introduced. Formalism for the independence of concepts...
Classification is a famous branch of machine learning. We have tried many ways to invent and improve algorithms to get better results from given data. However, few have been done on how to revise data to adapt machine learning. In this paper, the same classifiers are implemented on same object sets which are different in the granularity of classification to show different classification can make great...
Here, we propose a technique to acquire knowledge for baseball digest video production using an inductive inference approach. We integrated the concept of inductive logic programming (ILP) and baseball game metadata to enable learning of the highlight scene definition from digest video produced by a TV director.ILP is a learning method formed at the intersection of machine learning and logic programming,...
Ontology construction is a time consuming and labor intensive task and it is difficult to reuse existed ontology, so the conventional knowledge base based ontology building methods are in a low efficiency. From the view of facilitating knowledge sharing and reusing, modularization is introduced into ontology. But most current methods of ontology modularization are restricted to man-made factors to...
An experimental prototype system was created and used to investigate how information relevant to analyst queries, and constrained by a contextual model, can be found over a large information space. Agents employing the ant model sift through documents quickly using a transductive support machine classifier and return those meeting a classifier which is constantly refined through feedback from semantic...
Sem@ntica is a system for extracting the information contained in collections of documents into a knowledge base. It combines high quality conventional named entity analysis with an ontology class labeling capability for open class words. The ontology comprises an upper ontology and one or more domain ontologies. The system has tools for rapidly designing the ontology and mapping segments of Word...
In this paper, the focus is on how context information can be efficiently modeled with an ontology. This ontology can than be used by reasoning algorithms which are based on this context information. This is illustrated with a use case which studies the evolution from a place oriented to a person oriented nurse call system. An ontology was designed which holds the necessary context information. A...
This work describes the architectural framework of a clinical process management system. It supports the extraction, from textual documents, of ontologies, clinical processes and guidelines and allows their formal description using ontology and workflow representation languages. Clinical processes and guidelines are stored in a knowledge base and classified w.r.t. the concepts contained in the ontologies...
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