Ontology translation approaches for interoperability: A case study with Protege-2000 and WebODE

We describe four ontology translation approaches that can be used to exchange ontologies between ontology tools and/or ontology languages. These approaches are analysed with regard to two main features: how they preserve the ontology semantics after the translation process (aka semantic or consequence preservation) and how they allow final users and ontology-based applications to understand the resulting ontology in the target format (aka pragmatic preservation). These approaches are illustrated with practical examples that show how they can be applied to achieve interoperability between the ontology tools Protege-2000 and WebODE

Web structure mining of dynamic pages

Web structure mining in static web contents decreases the accuracy of mined outcomes and affects the quality of decision making activity. By structure mining in web hidden data, the accuracy ratio of mined outcomes can be improved, thus enhancing the reliability and quality of decision making activity. Data Mining is an automated or semi automated exploration and analysis of large volume of data in order to reveal meaningful patterns. The term web mining is the discovery and analysis of useful information from World Wide Web that helps web search engines to find high quality web pages and enhances web click stream analysis. One branch of web mining is web structure mining. The goal of which is to generate structural summary about the Web site and Web pages. Web structure mining tries to discover the link structure of the hyperlinks at the inter-document level. In recent years, Web link structure mining has been widely used to infer important information about Web pages. But a major part of the web is in hidden form, also called Deep Web or Hidden Web that refers to documents on the Web that are dynamic and not accessible by general search engines; most search engine spiders can access only publicly index able Web (or the visible Web). Most documents in the hidden Web, including pages hidden behind search forms, specialized databases, and dynamically generated Web pages, are not accessible by general Web mining applications. Dynamic content generation is used in modern web pages and user forms are used to get information from a particular user and stored in a database. The link structure lying in these forms can not be accessed during conventional mining procedures. To access these links, user forms are filled automatically by using a rule based framework which has robust ability to read a web page containing dynamic contents as activeX controls like input boxes, command buttons, combo boxes, etc. After reading these controls dummy values are filled in the available fields and the doGet or doPost methods are automatically executed to acquire the link of next subsequent web page. The accuracy ratio of web page hierarchical structures can phenomenally be improved by including these hidden web pages in the process of Web structure mining. The designed system framework is adequately strong to process the dynamic Web pages along with static ones

Método de modelagem do contexto estratégico para sistemas baseados em conhecimento

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2013.A Engenharia do Conhecimento dedica-se à modelagem de conhecimento e ao desenvolvimento de sistemas de conhecimento. Um de seus principais desafios está na compreensão do contexto de aplicação de seus métodos e técnicas e na conexão entre esses e o plano estratégico da organização beneficiada pelo projeto. Nesta dissertação, realizou-se pesquisa aplicada para estabelecer um método de modelagem do contexto estratégico para sistemas baseados em conhecimento (SBC). O método agrupa ferramentais, metodologias e técnicas de engenharia do conhecimento e ontologias, com o objetivo de contextualizar o conhecimento que forma a base de um SBC no plano estratégico de sua aplicação. O método tem fundamentos na visão sistêmica de Bunge (1997; 2000; 2004), ampliada pela abordagem de engenharia do conhecimento das metodologias CommonKADS e KAMET II (para identificação do contexto em que o conhecimento está inserido). A engenharia de ontologias é aplicada na representação formal do conhecimento, com o emprego de diretrizes e técnicas da metodologia NeOn e do método OntoKEM. O método foi aplicado em processo de explicitação do conhecimento contextual, em um projeto de pesquisa desenvolvimento e inovação. Os resultados da pesquisa corroboram com estudos que evidenciam os benefícios do conhecimento contextualizado para a compreensão do problema estratégico que envolve um SBC. Além disso, verificou-se que a identificação e modelagem do contexto estratégico pode servir, também, como fonte comum de conhecimento para as atividades técnicas de concepção de um SBC, tais como análises de viabilidade do sistema, extração de requisitos funcionais e requisitos não funcionais, elaboração de casos de uso e implantação de processos e cultura para viabilizar o desenvolvimento e uso de tais sistemas. Abstract : Knowledge Engineering is dedicated to the modeling of knowledge and the development of knowledge systems. One of the main challenges is to understand the context of applying methods and techniques, the connection between these and the strategic plan of the organization, in order to understand the potential benefits from the project. In this dissertation, we researched how to establish a method of modeling the strategic context for knowledge-based systems (KBS). The method combines tools, methodologies and techniques of knowledge engineering and ontologies in order to contextualize the knowledge that forms the basis of a strategic plan for applying the methods and techniques of KBS. The method has foundations in the systemic vision of Bunge (1997, 2000, 2004), supported by the approach of methodologies from knowledge engineering, like the CommonKADS and KAMET II methodologies (to identify the context of the knowledge being analysed). The ontology engineering is applied to the formal representation of knowledge, with the use of guidelines and techniques from the NEON methodology and from the OntoKEM method. The method was applied in the case study, in order to explain the contextual knowledge, in a research project of development and innovation. The survey results corroborate studies that show the benefits of contextual knowledge for understanding the strategic problem that involves a KBS. It was found that the identification and modeling of strategic context may also serve as a source of common knowledge to design the technical activities of an KBS, such as, analysis of feasibility from system development, extraction of functional and non-functional requirements. Furthermore can be serve for the elaboration of use cases, and implementation of processes and culture to enable the development and use of such systems