Subontology Extraction Using Hyponym and Hypernym Closure on is-a Directed Acyclic Graphs

International audienceOntologies are successfully used as semantic guides when navigating through the huge and ever increasing quantity of digital documents. Nevertheless, the size of numerous domain ontologies tends to grow beyond the human capacity to grasp information. This growth is problematic for a lot of key applications that require user interactions such as document annotation or ontology modification/evolution. The problem could be partially overcome by providing users with a sub-ontology focused on their current concepts of interest. A sub-ontology restricted to this sole set of concepts is of limited interest since their relationships can generally not be explicit without adding some of their hyponyms and hypernyms. This paper proposes efficient algorithms to identify these additional key concepts based on the closure of two common graph operators: the least common-ancestor and greatest common descendant. The resulting method produces ontology excerpts focused on a set of concepts of interest and is fast enough to be used in interactive environments. As an example, we use the resulting program, called OntoFocus (http://www.ontotoolkit.mines-ales.fr/), to restrict, in few seconds, the large Gene Ontology (~30,000 concepts) to a sub-ontology focused on concepts annotating a gene related to breast cancer

A framework for an adaptable and personalised e-learning system based on free web resources

An adaptable and personalised E-learning system (APELS) architecture is developed to provide a framework for the development of comprehensive learning environments for learners who cannot follow a conventional programme of study. The system extracts information from freely available resources on the Web taking into consideration the learners' background and requirements to design modules and a planner system to organise the extracted learning material to facilitate the learning process. The process is supported by the development of an ontology to optimise and support the information extraction process. Additionally, natural language processing techniques are utilised to evaluate a topic's content against a set of learning outcomes as defined by standard curricula. An application in the computer science field is used to illustrate the working mechanisms of the proposed framework and its evaluation based on the ACM/IEEE Computing Curriculum.A variety of models are developed and techniques used to support the adaptability and personalisation features of APELS. First, a learner’s model was designed by incorporating students’ details, students’ requirements and the domain they wish to study into the system. In addition, learning style theories were adopted as a way of identifying and categorising the individuals, to improve their on-line learning experience and applying it to the learner’s model. Secondly, the knowledge extraction model is responsible for the extraction of the learning resources from the Web that would satisfy the learners’ needs and learning outcomes. To support this process, an ontology was developed to retrieve the relevant information as per users’ needs. In addition, it transforms HTML documents to XHTML to provide the information in an accessible format and easier for extraction and comparison purposes. Moreover, a matching process was implemented to compute the similarity measure between the ontology concepts that are used in the ACM/IEEE Computer Science Curriculum and those extracted from the websites. The website with the highest similarity score is selected as the best matching website that satisfies the learners’ request. A further step is required to evaluate whether the content extracted by the system is the appropriate learning material of the subject. For this purpose, the learning outcome validation process is added to ensure that the content of the selected websites will enable the appropriate learning based to the learning outcomes set by standard curricula. Finally, the information extracted by the system will be passed to a Planner model that will structure the content into lectures, tutorials and workshops based on some predefined learning constraints. The APELS system provides a novel addition to the field of adaptive E-learning systems by providing more personalized learning material to each user in a time-efficient way saving his/her time looking for the right course from the hugely available resources on the Web or going through the large number of websites and links returned by traditional search engines. The APELS system will adapt better to the learner’s style based on feedback and assessment once the learning process is initiated by the learner. The APELS system is expected to develop over time with more users

Uma arquitetura para business intelligence baseada em tecnologias semânticas para suporte a aplicações analíticas

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de ProduçãoSoluções de Business Intelligence visam prover informação estratégica a partir das fontes de dados da organização. Entretanto, verificam-se desafios que permanecem não resolvidos nestas soluções no contexto da sociedade do conhecimento. Entre as principais deficiências das soluções atuais verificam-se a falta de perspectiva de utilização da semântica do negócio (i.e. sua terminologia e regras) no apoio ao processamento analítico e a falta de flexibilidade para a extensão das funcionalidades exploratórias de acordo com as especificidades de cada organização. Propõe-se uma arquitetura para BI - a arquitetura SBI - baseada em um novo paradigma que prevê a utilização intensiva do conhecimento do negócio para guiar o processamento analítico. A semântica do negócio na abordagem utilizada é representada em uma ontologia e mapeada aos dados e serviços em outras duas ontologias. O suporte à inferência sobre essa semântica é agregado aos módulos de gerenciamento de serviços e de análises da arquitetura, permitindo: a) extensão e composição de funcionalidades exploratórias através de Web services semânticos; b) recomendação de informação, serviços e inferências de acordo com o contexto da análise em um processo analítico-interativo assistido pela arquitetura; e c) manipulação de dados e serviços utilizando a terminologia do negócio. A viabilidade da proposta é demonstrada através do protótipo de ferramenta analítica OntoDSS, o qual é integrado a arquitetura SBI e aplicado em um estudo de caso no domínio da gestão de Ciência & Tecnologia. O ineditismo da contribuição está na busca de insumos na engenharia de conhecimento para prover alternativas de solução para as limitações nas soluções de BI atuais