59,898 research outputs found

    Cognitive Bias in Knowledge Engineering Course

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    The paper presents experience in teaching of knowledge and ontological engineering. The teaching framework is targeted on the development of cognitive skills that will allow facilitating the process of knowledge elicitation, structuring and ontology development for scaffolding studentsā€™ research. The structuring procedure is the kernel of ontological engineering. The 5-steps ontology designing process is described. Special stress is put on ā€œbeautificationā€ principles of ontology creating. The academic curriculum includes interactive game-format training of lateral thinking, interpersonal cognitive intellect and visual mind mapping techniques

    A community based approach for managing ontology alignments

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    The Semantic Web is rapidly becoming a defacto distributed repository for semantically represented data, thus leveraging on the added on value of the network effect. Various ontology mapping techniques and tools have been devised to facilitate the bridging and integration of distributed data repositories. Nevertheless, ontology mapping can benefitfrom human supervision to increase accuracy of results. The spread of Web 2.0 approaches demonstrate the possibility of using collaborative techniques for reaching consensus. While a number of prototypes for collaborative ontology construction are being developed, collaborative ontology mapping is not yet well investigated. In this paper, we describe a prototype that combines off-the-shelf ontology mapping tools with social software techniques to enable users to collaborate on mapping ontologies

    Integrating Web Services into Agentcities

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    This document describes how to make Web Services available to agents in an Agentcities environment and how to make agent-based services available to Web Service servers in a Web Services environment

    Directly depicting granular ontologies

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    Published in extended form as "Endurants and Perdurants in Directly Depicting Ontologies", We propose an ontological theory that is powerful enough to describe both complex spatio-temporal processes and the enduring entities that participate in such processes. For this purpose we distinguish between ontologies and metaontology. Ontologies are based on very simple directly depicting languages and fall into two major categories: ontologies of type SPAN and ontologies of type SNAP. These represent two complementary perspectives on reality and result in distinct though compatible systems of categories. In a SNAP (snapshot) ontology we have the enduring entities in a given domain as they exist to be inventoried at some given moment of time. In a SPAN ontology we have perduring entities such as processes and their parts and aggregates. We argue that both kinds of ontology are required, together with the meta-ontology which joins them together. On the level of meta-ontology we are able to impose constraints on ontologies of a sort which can support efļ¬cient processing of large amounts of data

    Querying a regulatory model for compliant building design audit

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    The ingredients for an effective automated audit of a building design include a BIM model containing the design information, an electronic regulatory knowledge model, and a practical method of processing these computerised representations. There have been numerous approaches to computer-aided compliance audit in the AEC/FM domain over the last four decades, but none has yet evolved into a practical solution. One reason is that they have all been isolated attempts that lack any form of standardisation. The current research project therefore focuses on using an open standard regulatory knowledge and BIM representations in conjunction with open standard executable compliant design workflows to automate the compliance audit process. This paper provides an overview of different approaches to access information from a regulatory model representation. The paper then describes the use of a purpose-built high-level domain specific query language to extract regulatory information as part of the effort to automate manual design procedures for compliance audit

    Enriched property ontology for knowledge systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Systems in Information Systems, Massey University, Palmerston North, New Zealand

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    "It is obvious that every individual thing or event has an indefinite number of properties or attributes observable in it and might therefore be considered as belonging to an indefinite number of different classes of things" [Venn 1876]. The world in which we try to mimic in Knowledge Based (KB) Systems is essentially extremely complex especially when we attempt to develop systems that cover a domain of discourse with an almost infinite number of possible properties. Thus if we are to develop such systems how do we know what properties we wish to extract to make a decision and how do we ensure the value of our findings are the most relevant in our decision making. Equally how do we have tractable computations, considering the potential computation complexity of systems required for decision making within a very large domain. In this thesis we consider this problem in terms of medical decision making. Medical KB systems have the potential to be very useful aids for diagnosis, medical guidance and patient data monitoring. For example in a diagnostic process in certain scenarios patients may provide various potential symptoms of a disease and have defining characteristics. Although considerable information could be obtained, there may be difficulty in correlating a patient's data to known diseases in an economic and efficient manner. This would occur where a practitioner lacks a specific specialised knowledge. Considering the vastness of knowledge in the domain of medicine this could occur frequently. For example a Physician with considerable experience in a specialised domain such as breast cancer may easily be able to diagnose patients and decide on the value of appropriate symptoms given an abstraction process however an inexperienced Physician or Generalist may not have this facility.[FROM INTRODUCTION

    Semantic Integration Portal

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    The Semantic Integration Portal is a demonstration of the potential capabilities of Semantic Web applications in a knowledge-rich context. Source data is taken from different online terrorist incident aggregators and marked up according to ontologies specific to those domains. Unlike other semantic web techniques, which scrape the internet for raw data and then mark-up against a standard ontology, the approach here is to allow each data source to have its own domain-specific ontology. This allows the data producers the opportunity to mark up their data in their own way, producing RDF data according to their own ontologies without the need to conform to a standard. A variety of semantic integration techniques can then be applied to these ontologies, both automatic and interactive, allowing data from both sets to be viewed in a suitable application, in this case the mspace browser. Future iterations of the semantic integration portal aim to introduce more automated ontology-mapping techniques, aligning data from a variety of diverse sources with less need for human intervention
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