Constructing and Extending Description Logic Ontologies using Methods of Formal Concept Analysis

Description Logic (abbrv. DL) belongs to the field of knowledge representation and reasoning. DL researchers have developed a large family of logic-based languages, so-called description logics (abbrv. DLs). These logics allow their users to explicitly represent knowledge as ontologies, which are finite sets of (human- and machine-readable) axioms, and provide them with automated inference services to derive implicit knowledge. The landscape of decidability and computational complexity of common reasoning tasks for various description logics has been explored in large parts: there is always a trade-off between expressibility and reasoning costs. It is therefore not surprising that DLs are nowadays applied in a large variety of domains: agriculture, astronomy, biology, defense, education, energy management, geography, geoscience, medicine, oceanography, and oil and gas. Furthermore, the most notable success of DLs is that these constitute the logical underpinning of the Web Ontology Language (abbrv. OWL) in the Semantic Web. Formal Concept Analysis (abbrv. FCA) is a subfield of lattice theory that allows to analyze data-sets that can be represented as formal contexts. Put simply, such a formal context binds a set of objects to a set of attributes by specifying which objects have which attributes. There are two major techniques that can be applied in various ways for purposes of conceptual clustering, data mining, machine learning, knowledge management, knowledge visualization, etc. On the one hand, it is possible to describe the hierarchical structure of such a data-set in form of a formal concept lattice. On the other hand, the theory of implications (dependencies between attributes) valid in a given formal context can be axiomatized in a sound and complete manner by the so-called canonical base, which furthermore contains a minimal number of implications w.r.t. the properties of soundness and completeness. In spite of the different notions used in FCA and in DLs, there has been a very fruitful interaction between these two research areas. My thesis continues this line of research and, more specifically, I will describe how methods from FCA can be used to support the automatic construction and extension of DL ontologies from data

Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

Ontologias na educação : uma proposta de aplicação em sistemas de recomendação

Esta pesquisa objetivou investigar contribuições das ontologias como modelos de representação de conhecimento em Sistemas de Recomendação (SRs) na Educação. O seu intuito foi a aplicação desse tipo de modelo em apoio a professores e alunos na utilização de SRs e a seleção e adaptação de uma metodologia para a modelagem de ontologias no contexto educacional. Constituindo-se em uma pesquisa de natureza aplicada, foi utilizada uma abordagem qualitativa. O seu público alvo consistiu em professores e profissionais no âmbito educacional, representados por alunos de cursos de pós-graduação. As atividades realizadas foram categorizadas em cinco etapas. Primeiramente foi realizado o estudo da literatura acadêmica atual compreendendo os seguintes temas: ontologias, metodologias de modelagem de ontologias, Sistemas de Recomendação; competências na educação. Em seguida foi selecionada uma metodologia de modelagem e utilizada na construção de uma ontologia de domínio para competências na educação. A terceira etapa consistiu nas avaliações da ontologia, em software, e da metodologia selecionada, através da sua utilização por alunos de uma disciplina de pós-graduação ministrada no primeiro semestre de 2017. Esses resultados permitiram adaptações realizadas na metodologia e na ontologia durante a quarta etapa de pesquisa. Por fim, a ontologia remodelada, intitulada OntoCompEdu, e a simulação da sua proposta de aplicação em um SR baseado em competências foram avaliadas através de software adequado. Na quinta etapa também foi validada a metodologia adaptada, intitulada MetOntoEdu, através da sua utilização por participantes da segunda edição da disciplina de pósgraduação ministrada, no primeiro semestre de 2018. A OntoCompEdu se mostrou válida para apoiar a utilização de SRs baseados em competências, além de apresentar potencial para aplicação em outros sistemas e propostas educacionais. A MetOntoEdu foi avaliada positivamente por seus usuários e na modelagem realizada nesta pesquisa. A OntoCompEdu e a MetOntoEdu serão disponibilizadas a comunidade acadêmica após a aprovação desta dissertação e foram projetadas de forma a apoiarem aplicações educacionais que extrapolam o contexto dos SRs.This work investigate the ontologies contribution as models of knowledge representation in Recommender Systems (RS) in Education. Its aim is to apply these models to support teachers and students in the RS use and the selection and adaptation of a methodology for ontologies modeling in the educational context. A qualitative approach was adopted to perform this applied nature research. Its target audience consisted of teachers and professionals in the educational field, represented by students of postgraduate courses. The conducted activities were categorized into five stages. Firstly, the current status of academic literature was rewied including the following topics: ontologies, ontology modeling methodologies, recommender systems and competencies in education. Secondly, a modeling methodology was selected and used to develop a domain ontology for competencies in education. The third stage consisted in the ontology evaluation by software and in the selected methodology testing through its use by postgraduate students, in 2017. Such results guided to methodology and ontology adaptations performed during the fourth research stage. Finally, in the fifth stage, the remodeled ontology was titled as OntoCompEdu and the simulation of its application proposal in a RS based on competencies were evaluated through suitable software. Simultaneously, the adapted methodology titled MetOntoEdu was also validated through its use by participants of the second edition of the postgraduate course, in 2018. OntoCompEdu proved to be valid to support the use of RS based on competencies. Moreover, it is suggested that this model has potential to be applied to other educational systems and proposals. MetOntoEdu was positively evaluated by its users and as well as OntoCompEdu will be available to academic community after this dissertation approval, thus contributing to educational applications beyond the RS context

Epidemiology of Injury in English Women's Super league Football: A Cohort Study

INTRODUCTION: The epidemiology of injury in male professional football has been well documented (Ekstrand, Hägglund, & Waldén, 2011) and used as a basis to understand injury trends for a number of years. The prevalence and incidence of injuries occurring in womens super league football is unknown. The aim of this study is to estimate the prevalence and incidence of injury in an English Super League Women’s Football squad. METHODS: Following ethical approval from Leeds Beckett University, players (n = 25) signed to a Women’s Super League Football club provided written informed consent to complete a self-administered injury survey. Measures of exposure, injury and performance over a 12-month period was gathered. Participants were classified as injured if they reported a football injury that required medical attention or withdrawal from participation for one day or more. Injuries were categorised as either traumatic or overuse and whether the injury was a new injury and/or re-injury of the same anatomical site RESULTS: 43 injuries, including re-injury were reported by the 25 participants providing a clinical incidence of 1.72 injuries per player. Total incidence of injury was 10.8/1000 h (95% CI: 7.5 to 14.03). Participants were at higher risk of injury during a match compared with training (32.4 (95% CI: 15.6 to 48.4) vs 8.0 (95% CI: 5.0 to 10.85)/1000 hours, p 28 days) of which there were three non-contact anterior cruciate ligament (ACL) injuries. The epidemiological incidence proportion was 0.80 (95% CI: 0.64 to 0.95) and the average probability that any player on this team will sustain at least one injury was 80.0% (95% CI: 64.3% to 95.6%) CONCLUSION: This is the first report capturing exposure and injury incidence by anatomical site from a cohort of English players and is comparable to that found in Europe (6.3/1000 h (95% CI 5.4 to 7.36) Larruskain et al 2017). The number of ACL injuries highlights a potential injury burden for a squad of this size. Multi-site prospective investigations into the incidence and prevalence of injury in women’s football are require