Thesis (M.C.S.)--Miami University, Dept. of Computer Science and Systems Analysis, 2009. / Title from first page of PDF document. Includes bibliographical references (p. 122-123).

Στα πλαίσια της παρούσης διδακτορικής διατριβής, εξετάζονται σύγχρονες μεθοδολογίες αναπαράστασης και διαχείρισης γνώσης όπως οι οντολογίες. Επίσης, εξετάζονται σύγχρονες μεθοδολογίες ανακάλυψης και διανομής γνώσης και περιεχομένου όπως οι ευφυείς διαμεσολαβητές (intelligent agents). Μαζί με τα ανωτέρω, εξετάζονται αλγόριθμοι ανάκτησης γνώσης από πολύ μεγάλους όγκους δεδομένων, αναπαριστάμενων υπό την μορφή οντολογιών και δενδρικών δομών υπό την έννοια ταξινομημένων γράφων, βάσει πιο κλασσικών μεθοδολογιών και μοντέλων που αφορούν και αναπτύχθηκαν κυρίως για επιχειρηματικά δεδομένα, όπως είναι οι αλγόριθμοι ταξινόμησης, ομαδοποίησης και συσχέτισης. Η παρούσα Δ.Δ. εξετάζει επίσης με βάση τις ανωτέρω μεθοδολογίες την «ομοιότητα» (similarity) κατανόησης εννοιών σε κάποιο ορισμένο πεδίο γνώσης από συγκεκριμένους χρήστες του πεδίου αυτού. Στη συνέχεια, προτείνει μία μεθοδολογία αυτόματης ανταλλαγής δομημένου περιεχομένου και εννοιών μεταξύ αυτών, ανάλογα των κοινών ή μη ενδιαφερόντων τους. Το σύστημα αναπτύσσεται σε θεωρητικό επίπεδο στην μεθοδολογία ONARM και υλοποιείται σε επίπεδο λογισμικού με βάση την προτεινόμενη μεθοδολογία στο σύστημα Concept Net. / In the frame of the present PhD dissertation, it is examined the complex problem of knowledge representation and management and methodologies relevant methodologies like the ontologies and intelligent agents. In this frame complex algorithms for knowledge acquisition and representation are examined from very large data volumes, that are represented in terms of ontological graphs (trees – taxonomies), in conjunction with more classical methodologies like algorithm for association, clustering and categorization. Based on these, the present work proposes the ONARM methodology, focusing in the intelligent understanding of concepts and the intelligent exchange of content, based on concept similarity principles. Then, based on the ONARM theoretical background, build the software platform CONCEPT NET in the domain of tourism.

Η έρευνα αναφορικά με την εξέλιξη του Παγκόσμιου Ιστού (WWW) κινείται τα τελευταία χρόνια προς πιο ευφυείς και αυτοματοποιημένους τρόπους ανακάλυψης και εξαγωγής της πληροφορίας. Ο Σημαντικός Ιστός (Semantic Web) είναι μία επέκταση του σημερινού Ιστού, όπου στην πληροφορία δίνεται σαφώς προσδιορισμένη σημασία, δίνοντας έτσι τη δυνατότητα στις μηχανές να μπορούν πλέον να επεξεργάζονται καλύτερα και να «κατανοούν» τα δεδομένα, τα οποία μέχρι σήμερα απλώς παρουσιάζουν. Για να λειτουργήσει ο Σημαντικός Ιστός, οι υπολογιστές θα πρέπει να έχουν πρόσβαση σε οργανωμένες συλλογές πληροφοριών, που καλούνται οντολογίες (ontologies). Οι οντολογίες παρέχουν μια μέθοδο αναπαράστασης της γνώσης στο Σημαντικό Ιστό και μπορούν επομένως να αξιοποιηθούν από τα υπολογιστικά συστήματα για τη διεξαγωγή αυτοματοποιημένου συλλογισμού (automated reasoning). Για την περιγραφή και την αναπαράσταση των οντολογιών του Σημαντικού Ιστού σε γλώσσες αναγνώσιμες από τη μηχανή, έχουν προταθεί και βρίσκονται υπό εξέλιξη διάφορες πρωτοβουλίες, με πιο σημαντική τη Γλώσσα Οντολογίας Ιστού (Web Ontology Language – OWL). H γλώσσα αυτή αποτελεί πλέον τη βάση για την αναπαράσταση γνώσης στο Σημαντικό Ιστό, λόγω της προώθησής της από το W3C, και του αυξανόμενου βαθμού υιοθέτησής της στις σχετικές εφαρμογές. Το βασικότερο εργαλείο για την υλοποίηση εφαρμογών που διαχειρίζονται OWL οντολογίες, είναι το OWL API. Το OWL API αποτελείται από προγραμματιστικές βιβλιοθήκες και μεθόδους, οι οποίες παρέχουν μια υψηλού επιπέδου διεπαφή για την πρόσβαση και τον χειρισμό OWL οντολογιών. Το θεωρητικό υπόβαθρο που εγγυάται την εκφραστική και συλλογιστική ισχύ των οντολογιών, παρέχεται από τις Λογικές Περιγραφής (Description Logics). Οι Λογικές Περιγραφής αποτελούν ένα καλώς ορισμένο αποφασίσιμο υποσύνολο της Λογικής Πρώτης Τάξης και καθιστούν δυνατή την αναπαράσταση και ανακάλυψη γνώσης στο Σημαντικό Ιστό. Για την ανακάλυψη άρρητης πληροφορίας ενδείκνυται, επομένως, να αξιοποιηθούν συστήματα βασισμένα σε Λογικές Περιγραφής. Τα συστήματα αυτά ονομάζονται και εργαλεία Συλλογισμού (Reasoners). Χαρακτηριστικά παραδείγματα τέτοιων εργαλείων αποτελούν τα FaCT++ και Pellet. Από τα παραπάνω γίνεται προφανής ο λόγος για τον οποίο, τόσο το OWL API, όσο και τα εργαλεία Συλλογισμού, χρησιμοποιούνται από προτεινόμενα μοντέλα υλοποίησης εφαρμογών του Σημαντικού Ιστού επόμενης γενιάς (WEB 3.0), για την επικοινωνία και την υποβολή «έξυπνων» ερωτημάτων σε βάσεις γνώσης (knowledge bases). Στα μοντέλα αυτά προτείνεται, επίσης, η χρήση κατανεμημένης αρχιτεκτονικής 3-επιπέδων (3-tier distributed architecture), για την υλοποίηση εφαρμογών του Σημαντικού Ιστού. Σκοπός της διπλωματικής αυτής είναι ο σχεδιασμός και η ανάπτυξη μιας διεπαφής Πελάτη – Εξυπηρετητή (Client – Server interface) για την υποστήριξη υπηρεσιών Συλλογισμού (reasoning) σε κατανεμημένες εφαρμογές του Σημαντικού Ιστού. Πιο συγκεκριμένα, η διεπαφή που θα υλοποιήσουμε αποτελείται από δύο μέρη. Το πρώτο παρέχει τα απαραίτητα αρχεία για την εκτέλεση ενός εργαλείου Συλλογισμού σε κάποιο απομακρυσμένο μηχάνημα (Server). Με τον τρόπο αυτό, το συγκεκριμένο μηχάνημα θα παρέχει απομακρυσμένες (remote) υπηρεσίες Συλλογισμού. Το δεύτερο μέρος (Client) περιέχει αρχεία, που δρουν συμπληρωματικά στις βιβλιοθήκες του OWL API, και του δίνουν νέες δυνατότητες. Συγκεκριμένα, δίνουν την δυνατότητα σε μια εφαρμογή, που είναι υλοποιημένη με το OWL API, να χρησιμοποιήσει τις υπηρεσίες που προσφέρονται από κάποιο απομακρυσμένο εργαλείο Συλλογισμού. Συνεπώς, η διεπαφή μας θα δώσει την δυνατότητα υιοθέτησης της χρήσης του OWL API και των εργαλείων Συλλογισμού από κατανεμημένες αρχιτεκτονικές για την υλοποίηση εφαρμογών του Σημαντικού Ιστού. / In the past few years, the research that focus on the development of the World Wide Web (WWW) has moved towards more brilliant and automated ways of discovering and exporting the information. The Semantic Web is an extension of the current Web, that explicitly defines the information, thus providing the machines with the possibility to better process and “comprehend” the data, which until now they simply present. For the Semantic Web to function properly, computers must have access to organized collections of information, that are called ontologies. Ontologies provide a method of representing knowledge in the Semantic Web and, consequently, they can be used by computing systems in order to conduct automated reasoning. In order to describe and represent the ontologies of the Semantic Web in machine-readable language, various initiatives have been proposed and are under development, most important of which is the Web Ontology Language - OWL. This language constitutes the base for representing knowledge in the Semantic Web, due to its promotion from the W3C, and its increasing degree of adoption from relative applications. The main tool for the development of applications that manages OWL ontologies, is the OWL API. The OWL API consists of programming libraries and methods, that provide a higher-level interface for accessing and handling OWL ontologies. The theoretical background that guarantees the expressivity and the reasoning of ontologies, is provided from Description Logics. Description Logics constitute a well defined and decidable subset of First Order Logic and make possible the representation and discovery of knowledge in the Semantic Web. As a consequence, in order to discover “clever” information, we have to develop and use systems that are based in Description Logics. These systems are also called Reasoners. Characteristic examples of such tools are FaCT++ and Pellet. From above, it must be obvious why both the OWL API and the Reasoners are used by proposed models of developing next generation (WEB 3.0) Semantic Web applications, for the communication and the submission of “intelligent” questions in knowledge bases. These models also propose the use of a 3-level distributed architecture (3-tier distributed architecture), for the development of Semantic Web applications. Aim of this diploma thesis is to design and implement a Client-Server interface to support Reasoning in distributed applications of the Semantic Web. Specifically, the interface that we will implement consists of two parts. First part provides the essential files for a Reasoner to run in a remote machine (Server). As a result, this machine will provide remote Reasoning services. Second part (Client) contains files, that act additionally to (enhance) the libraries of the OWL API, and give them new features. More precisely, they provide an application, that is implemented with OWL API, with the possibility of using the services that are offered by a remote Reasoner. Consequently, our interface will make possible the use of the OWL API and the Reasoners from proposed distributed architectures for the development of Semantic Web applications.

Τα μελλοντικά περιβάλλοντα υπολογισμού περιλαμβάνουν την ενσωμάτωση καθημερινών αντικειμένων, εφοδιασμένα με μικροσκοπικούς επεξεργαστές, αισθητήρες και κάρτες ασύρματων δικτύων. Τα έξυπνα αυτά αντικείμενα (τεχνουργήματα) μπορούν να εξερευνούν το περιβάλλον στο οποίο βρίσκονται και να επικοινωνούν μεταξύ τους. Η διαδραστικότητα με τον άνθρωπο μπορεί να παρέχει τη δυνατότητα αντιμετώπισης διαφόρων εργασιών με διαισθητικό τρόπο. Γίνεται αντιληπτό ότι μέσα σε ένα τέτοιο περιβάλλον, προκύπτουν σοβαρά ζητήματα που σχετίζονται με την ιδιωτικότητα των χρηστών. Αρχικά, εξαιτίας της αορατότητας των υπολογισμών που έχει σαν αποτέλεσμα οι χρήστες να μην τους αντιλαμβάνονται και έτσι να μην αισθάνονται ασφαλείς στο περιβάλλον αυτό. Επιπλέον, η παροχή ορισμένων υπηρεσιών απαιτεί τη μετάδοση και επεξεργασία προσωπικών δεδομένων και, ως εκ τούτου, εγκυμονεί κινδύνους για την προσωπική ζωή. Στην παρούσα εργασία ένα τέτοιο περιβάλλον (περιβάλλον περιρρέουσας νοημοσύνης) με τα παραπάνω χαρακτηριστικά, μοντελοποιείται μέσω των σφαιρών δραστηριοτήτων. Μια σφαίρα δραστηριοτήτων περιλαμβάνει όλη εκείνη την πληροφορία που απαιτείται για να εκτελεστεί μια συγκεκριμένη εργασία μέσα στο περιβάλλον. Στόχος της εργασίας είναι η μοντελοποίηση πολιτικών ιδιωτικότητας με κέντρο το χρήστη, η οποία μπορεί να πραγματοποιηθεί σε μια σφαίρα σε οποιοδήποτε περιβάλλον περιρρέουσας νοημοσύνης. Για να επιτευχθεί σημασιολογική ομοιογένεια, παρά την πιθανή ετερογένεια των πόρων ενός τέτοιου συστήματος, έχει σχεδιαστεί μια οντολογία για την αναπαράσταση αυτών των πολιτικών. Επιπλέον το σημασιολογικό αυτό πλαίσιο μοντελοποιεί τις βασικές αρχές και τους κανόνες αναφορικά με την προστασία των προσωπικών δεδομένων και την ιδιωτικότητα. Η προτεινόμενη οντολογία αξιολογείται βάσει αναγνωρισμένων κριτηρίων όπως είναι οι ερωτήσεις επάρκειας / Future computing environments involve integrating everyday objects equipped with tiny processors, sensors and wireless network cards. These smart objects (artifacts) may explore their environment and communicate with each other. Interactivity with humans may provide the ability of dealing with tasks in an intuitive way. It is clear that within this environment, serious issues related to the privacy of the users arise. Initially, due to the invisibility of all computations which results to the users being unaware of them. Moreover, the provision of certain services requires the transmission and processing of user’s personal data and thus poses a serious threat to their privacy. In the present project such an environment (ambient intelligence environment) with the above characteristics, is modeled through the concept of activity spheres. An activity sphere contains all the necessary information needed to realize a specific task within this environment. The aim of the project is to model a user-centered privacy policy which could be realized for a sphere in any ambient intelligence environment it is instantiated. To achieve semantic homogeneity, despite the possible heterogeneity of the resources within such an environment, an ontology has been designed. Furthermore, this semantic framework, models the fundamental principles and rules regarding personal data protection and privacy. The proposed ontology is evaluated by means of well-appreciated criteria such as competency questions

Ontologias representam uma conceitualização compartilhada de uma comunidade de conhecimento. São construídas a partir da descrição dos significados dos conceitos, descritos através de seus atributos e dos relacionamentos entre os conceitos. Conceitos se referem ao objeto da conceitualização, o universo do discurso. São caracterizados por seus atributos e domínios de valores possíveis. Relacionamentos são utilizados para descreverem de que forma os conceitos se estruturam no mundo. Nas ontologias todos os conceitos são hierarquicamente definidos, porém existem outros relacionamentos que são definicionais, dando identidade aos conceitos e sentido ao mundo. Além dos relacionamentos de subsunção que constroem as taxonomias de conceitos, outras relações formais e materiais auxiliam na estruturação do domínio e na definição conceitual. As ferramentas de modelagem, no entanto, ainda são falhas em diferenciar os vários tipos de relacionamentos formais e materiais para atribuir as possibilidades de raciocínio automático. Em especial, relacionamentos mereológicos e partonômicos carecem de opções de implementação que permitam extrair o potencial semântico da modelagem. Este projeto de pesquisa tem como ponto de partida o estudo da literatura sobre ontologias e relações, em especial sobre relações formais e materiais, incluindo relações mereológicas e partonômicas, revisando os princípios encontrados nas ontologias. Além disso, nós identificamos os fundamentos teóricos das relações e analisamos a aplicação dos conceitos das relações sobre as principais ontologias de fundamentação em prática na atualidade. Na sequência, a partir das propostas levantadas, este trabalho propõe uma alternativa para a modelagem conceitual destas relações em uma ontologia de domínio visual. Esta alternativa foi disponibilizada na ferramenta de construção de ontologias do Projeto Obaitá, a qual está sendo desenvolvida pelo Grupo de Pesquisa de Bancos de Dados Inteligentes (BDI) da UFRGS. / Ontologies represent a shared conceptualization of a knowledge community. They are built from the description of the meaning of concepts, expressed through their attributes and their relationships. Concepts refer to the object of conceptualization, the universe of discourse. They are characterized by their attributes and domains of possible values. Relationships are used to describe how the concepts are structured in the world. In ontologies all concepts are hierarchically defined, however there are other relationships that are definitional, giving identity to the concepts and meaning to the world. In addition to the subsumption relationships that build the taxonomies of concepts, other formal and material relations assist in structuring the domain and the conceptual definition. The modeling tools, however, are still deficient in differentiating the various types of formal and material relationships in order to assign the possibilities of automated reasoning. In particular, mereological and partonomic relationships lack of implementation options that allow extracting the semantic potential when modeling. This research project takes as a starting point the study of the literature on ontologies and relations, especially on formal and material relations, including mereological and partonomic relations, reviewing the principles found on ontologies. Furthermore, we identify the theoretical foundations of the relations and analyze the application of the relations concepts to the main foundational ontologies in use nowadays. Following, from the raised proposals, this work proposes an alternative for the conceptual modeling of these relations in a visual domain ontology. This alternative has been made available on the ontology building tool of the Obaitá Project, which is under development by the Intelligent Databases Research Group (BDI) from UFRGS.

É usual falar da onipresença dos documentos de texto e na quantidade de informação não estruturada, armazenada sob a forma de arquivos com documentos de texto em linguagem natural. Este fato torna-se mais dramático no domínio jurídico, onde o texto é a ferramenta básica de trabalho dos profissionais da área, tanto na forma das fontes de consulta, i.e., a legislação, como no principal produto da atividade jurídica, especificamente a criação de documentos escritos. Desde a invenção do editor de texto existem iniciativas de utilização de tecnologias da informação para auxiliar a geração, armazenamento e consulta de documentos jurídicos. Dentre os diversos ramos da atividade jurídica, a criação de contratos é especialmente importante, devido a sua onipresença nas interações entre os agentes sociais, sejam elas pessoas físicas, jurídicas ou agentes de governo. Com foco na criação de modelos de contratos, este trabalho introduz a linguagem gráfica GraphSchema. Projetada para usuários finais, GraphSchema utiliza uma representação visual para criação de modelos de contratos jurídicos, permitindo a modelagem dos conceitos, relacionamentos e restrições entre estes. A representação visual é diretamente mapeada na linguagem SML, uma extensão do XML Schema. Ao possibilitar a criação de modelos conceituais de contratos diretamente por parte dos usuários finais sem forçar um vocabulário ou ontologia específicos, GraphSchema e, conseqüentemente, a utilização de SML, apresenta vantagens quando comparado com a utilização de XML Schema, RDF e OWL. Mas principalmente apresenta vantagens quando comparada com outras abordagens baseadas em definição de vocabulários e utilização de ontologias formais. Estas vantagens decorrem de sua simplicidade e flexibilidade que permite a utilização de padrões existentes para a definição de modelos de contratos, tais como, o padrão eContracts definido pelo consórcio LegalXML. Deste modo, GraphSchema apresenta-se como uma opção para a implementação e aplicação prática deste padrão. A disponibilidade de uma linguagem para usuários não técnicos permitirá a criação de contratos com marcação a priori, quando utilizado em conjunto com editores de texto guiados por XML. Isto irá abrir caminho para o aumento da produtividade na criação de contratos e documentos jurídicos. / It is common place to talk about the widespread presence of text documents and unstructured information stored in natural language text documents file format. This fact is still more dramatic to law professionals where text is the basic tool for their work. Those texts came from multiple sources like research documents and legislation and also are the main product from law activities, i.e., text documents which are created by law professionals. Since the first text editor there are several initiatives to use information technologies to help the generation, storage and search of law documents. From all documents, legal contracts generation is especially important due to its ubiquity and use by all social actors like common people, companies and government agencies. This work main focus is legal contract model generation. GraphSchema graphical language is introduced as a proposed solution to enable users to create contract models without help from a computer professional. It uses a visual representation to create legal contracts models, where concepts, relationships between those and constraints can be represented in a visual paradigm which can be understood by users. The graphical representation is translated to SML, a XML Schema extension. On enabling final user conceptual contract modeling without forcing a restrict vocabulary or ontology, GraphSchema and. by consequence, the use of SML, has several advantages in comparison with the use of simple XML Schema, RDF and OWL. But mainly show advantages when compared with other approaches based on vocabulary definition and formal ontology usage. Those advantages are mainly due to its simplicity and flexibility which enable the use of existing standards to define contract models like the eContracts standard defined by LegalXML consortium. This way, GraphSchema appears as an option to implement and use this standard in real world cases. The availability of a language directed towards non technical user will enable the contracts creation with tag markup from the beginning when used with XML guided text editors. This opens a door to productivity grow on contracts and legal documents creation.

Four relatively separate topics are presented in the thesis. Each topic represents one particular aspect of the Information Extraction discipline. The first two topics are focused on our information extraction methods based on deep language parsing. The first topic relates to how deep language parsing was used in our extraction method in combination with manually designed extraction rules. The second topic deals with a method for automated induction of extraction rules using Inductive Logic Programming. The third topic of the thesis combines information extraction with rule based reasoning. The core of our extraction method was experimentally reimplemented using semantic web technologies, which allows saving the extraction rules in so called shareable extraction ontologies that are not dependent on the original extraction tool. The last topic of the thesis deals with document classification and fuzzy logic. We are investigating the possibility of using information obtained by information extraction techniques to document classification. Our implementation of so called Fuzzy ILP Classifier was experimentally used for the purpose of document classification.

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No. of bitstreams: 1 IngridyMPB_DISSERT.pdf: 7607381 bytes, checksum: c08a68ab4cbff8326651716b5e44e1d8 (MD5) Previous issue date: 2018-02-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The use of mobile devices for the continuous monitoring of patients with a particular pathology may benefit in their prevention, diagnosis and treatment. The objective of this work is the construction of a Medical Assistance Equipment (EMA) for the monitoring of patients with pathology related to di culty in the food intake process and/or Oropharyngeal Dysphagia. The EMA works by capturing the movements and sound signals generated during the chewing and swallowing process and, from this, identifies the physical type of the food, classifying it as: i) liquid; ii) pasty; iii) solid. It is important to emphasize the requirements for a construction of EMA were taken from the context of Dysphagia. After a classification, the information is stored generating a food history, with detailed information about the meals performed and the distribution of Dysphagia that the patient is. To this end, a domain ontology was implemented with logical axioms capable of classifying the type of physical material of the swallowed food based on the analysis of the data captured during the swallowing process. In order to analyze the results generated by the EMA, experiments were carried out in a real environment with 10 participants, authorized by the ethics committee under the following opinion number: 2.332.026. Each participant was invited to swallow liquid, pasty and solid foods. The data generated by the participants were analyzed and classified by the developed ontology. At the end, the results presented 100% of correct answers in relation to experiments with solid foods, 80% of correct answers in experiments with liquid foods and 75% of correct answers in relation to experiments with pasty foods. A general analysis of the EMA presented the safety area of 85%. Finally, the EMA provided relevant results regarding correct classification of data. Thus, a medical team can monitor, from a distance, the patient’s evolution onwards, the detailed information available, not EMA, facilitating the monitoring process and improving a quality of life of patients requiring remote monitoring / O uso de dispositivos móveis para o monitoramento contínuo de pacientes com uma determinada patologia pode beneficiar significativamente em sua prevenção, diagnóstico e tratamento. O objetivo deste trabalho é a construção de um Equipamento Médico Assistencial (EMA) para o monitoramento de pacientes com alguma patologia relacionada à dificuldade no processo de ingestão de alimentos e/ou Disfagia Orofaríngea. O EMA funciona através da captura dos movimentos e dos sinais sonoros gerados durante o processo de mastigação e deglutição, e, a partir disso, identifica o tipo físico do alimento, classificando-o em: i) líquido; ii) pastoso; iii) sólido. É importante ressaltar que os requisitos definidos para a construção do EMA foram retirados do contexto da Disfagia. Após a classificação, essas informações são armazenadas gerando um histórico alimentar com informações detalhadas sobre as refeições realizadas e o nível de Disfagia que o paciente se encontra. Para este fim, foi implementada uma ontologia de domínio com axiomas lógicos capazes de classificar o tipo físico do alimento deglutido tendo por base a análise dos dados capturados durante o processo de deglutição. Com o intuito de analisar os resultados gerados pelo EMA, foram realizados experimentos em ambiente real com 10 participantes, autorizado pelo comitê de ética sob o seguinte número de parecer: 2.332.026. Cada participante foi convidado a deglutir alimentos líquidos, pastosos e sólidos. Os dados gerados pelos participantes foram analisados e classificados pela ontologia desenvolvida. Ao final, os resultados apresentam 100% de acerto em relação aos experimentos realizados com alimentos sólidos, 80% de acerto em relação aos experimentos realizados com alimentos líquidos e 75% de acerto em relação aos experimento realizados com alimentos pastosos. A análise geral do EMA apresentou o nível de acurácia de 85%. Por fim, o EMA proporcionou resultados relevantes quanto à classificação correta de dados. Assim, a equipe médica pode acompanhar, a distância, a evolução do paciente diante das informações detalhadas disponíveis no EMA, facilitando o processo de monitoramento e melhorando a qualidade de vida dos pacientes que necessitam de acompanhamento a distância / 2018-06-14

[pt] Este trabalho aborda problemas de projeto de ontologias tratando-as como teorias e definindo um conjunto de operações que mapeiam ontologias em ontologias, incluindo suas restrições. Inicialmente, o trabalho resume o conhecimento básico necessário para definir a classe de ontologias utilizada e propõe quatro operações para manipular ontologias. Em seguida, mostra o funcionamento destas operações e como elas podem ajudar na criação de novas ontologias. O cerne do trabalho mostra a implementação destas operações em um plug-in do Protégé, detalhando sua arquitetura e incluindo casos de uso. / [en] This work addresses ontology design problems by treating ontologies as theories and by defining a set of operations that map ontologies into ontologies, including their constraints. The work first summarizes the base knowledge needed to define the class of ontologies used and proposes four operations to manipulate them. It then shows how the operations work and how they may help design new ontologies. The core of this work is describing the implementation of the operations over a Protégé plug-in, detailing the architecture and including case-use examples.

É usual falar da onipresença dos documentos de texto e na quantidade de informação não estruturada, armazenada sob a forma de arquivos com documentos de texto em linguagem natural. Este fato torna-se mais dramático no domínio jurídico, onde o texto é a ferramenta básica de trabalho dos profissionais da área, tanto na forma das fontes de consulta, i.e., a legislação, como no principal produto da atividade jurídica, especificamente a criação de documentos escritos. Desde a invenção do editor de texto existem iniciativas de utilização de tecnologias da informação para auxiliar a geração, armazenamento e consulta de documentos jurídicos. Dentre os diversos ramos da atividade jurídica, a criação de contratos é especialmente importante, devido a sua onipresença nas interações entre os agentes sociais, sejam elas pessoas físicas, jurídicas ou agentes de governo. Com foco na criação de modelos de contratos, este trabalho introduz a linguagem gráfica GraphSchema. Projetada para usuários finais, GraphSchema utiliza uma representação visual para criação de modelos de contratos jurídicos, permitindo a modelagem dos conceitos, relacionamentos e restrições entre estes. A representação visual é diretamente mapeada na linguagem SML, uma extensão do XML Schema. Ao possibilitar a criação de modelos conceituais de contratos diretamente por parte dos usuários finais sem forçar um vocabulário ou ontologia específicos, GraphSchema e, conseqüentemente, a utilização de SML, apresenta vantagens quando comparado com a utilização de XML Schema, RDF e OWL. Mas principalmente apresenta vantagens quando comparada com outras abordagens baseadas em definição de vocabulários e utilização de ontologias formais. Estas vantagens decorrem de sua simplicidade e flexibilidade que permite a utilização de padrões existentes para a definição de modelos de contratos, tais como, o padrão eContracts definido pelo consórcio LegalXML. Deste modo, GraphSchema apresenta-se como uma opção para a implementação e aplicação prática deste padrão. A disponibilidade de uma linguagem para usuários não técnicos permitirá a criação de contratos com marcação a priori, quando utilizado em conjunto com editores de texto guiados por XML. Isto irá abrir caminho para o aumento da produtividade na criação de contratos e documentos jurídicos. / It is common place to talk about the widespread presence of text documents and unstructured information stored in natural language text documents file format. This fact is still more dramatic to law professionals where text is the basic tool for their work. Those texts came from multiple sources like research documents and legislation and also are the main product from law activities, i.e., text documents which are created by law professionals. Since the first text editor there are several initiatives to use information technologies to help the generation, storage and search of law documents. From all documents, legal contracts generation is especially important due to its ubiquity and use by all social actors like common people, companies and government agencies. This work main focus is legal contract model generation. GraphSchema graphical language is introduced as a proposed solution to enable users to create contract models without help from a computer professional. It uses a visual representation to create legal contracts models, where concepts, relationships between those and constraints can be represented in a visual paradigm which can be understood by users. The graphical representation is translated to SML, a XML Schema extension. On enabling final user conceptual contract modeling without forcing a restrict vocabulary or ontology, GraphSchema and. by consequence, the use of SML, has several advantages in comparison with the use of simple XML Schema, RDF and OWL. But mainly show advantages when compared with other approaches based on vocabulary definition and formal ontology usage. Those advantages are mainly due to its simplicity and flexibility which enable the use of existing standards to define contract models like the eContracts standard defined by LegalXML consortium. This way, GraphSchema appears as an option to implement and use this standard in real world cases. The availability of a language directed towards non technical user will enable the contracts creation with tag markup from the beginning when used with XML guided text editors. This opens a door to productivity grow on contracts and legal documents creation.