For researches in the field of the data mining and machine learning the necessary condition is an availability of various input data set. Now researchers create the databases of such sets. Examples of the following systems are: The UCI Machine Learning Repository, Data Envelopment Analysis Dataset Repository, XMLData Repository, Frequent Itemset Mining Dataset Repository. Along with above specified statistical repositories, the whole pleiad from simple filestores to specialized repositories can be used by researchers during solution of applied tasks, researches of own algorithms and scientific problems. It would seem, a single complexity for the user will be search and direct understanding of structure of so separated storages of the information. However detailed research of such repositories leads us to comprehension of deeper problems existing in usage of data. In particular a complete mismatch and rigidity of data files structure with SDMX - Statistical Data and Metadata Exchange - standard and structure used by many European organizations, impossibility of preliminary data origination to the concrete applied task, lack of data usage history for those or other scientific and applied tasks. Now there are lots of methods of data miming, as well as quantities of data stored in various repositories. In repositories there are no methods of DM (data miming) and moreover, methods are not linked to application areas. An essential problem is subject domain link (problem domain), methods of DM and datasets for an appropriate method. Therefore in this work we consider the building problem of ontological models of DM methods, interaction description of methods of data corresponding to them from repositories and intelligent agents allowing the statistical repository user to choose the appropriate method and data corresponding to the solved task. In this work the system structure is offered, the intelligent search agent on ontological model of DM methods considering the personal inquiries of the user is realized. For implementation of an intelligent data and metadata exchange repository the agent oriented approach has been selected. The model uses the service oriented architecture. Here is used the cross platform programming language Java, multi-agent platform Jadex, database server Oracle Spatial 10g, and also the development environment for ontological models - Protégé Version 3.4.

<p>У дисертацији је представљен прототип агентског, домен-оријентисаног језика ALAS. Основни мотиви развоја ALAS језика су подршка дистрибуираном не-аксиоматском резоновању као и омогућавање интероперабилности и хетерогене мобилности Siebog агената јер је приликом анализе постојећих агентских домен-оријентисаних језика утврђено да ни један језик не подржава ове захтеве. Побољшање у односу на сличне постојеће агентске, домен-оријентисане језике огледа се и у програмским конструктима које нуди ALAS језик а чија је основна сврха писање концизних агената који се извршавају у специфичним доменима.</p> / <p>U disertaciji je predstavljen prototip agentskog, domen-orijentisanog jezika ALAS. Osnovni motivi razvoja ALAS jezika su podrška distribuiranom ne-aksiomatskom rezonovanju kao i omogućavanje interoperabilnosti i heterogene mobilnosti Siebog agenata jer je prilikom analize postojećih agentskih domen-orijentisanih jezika utvrđeno da ni jedan jezik ne podržava ove zahteve. Poboljšanje u odnosu na slične postojeće agentske, domen-orijentisane jezike ogleda se i u programskim konstruktima koje nudi ALAS jezik a čija je osnovna svrha pisanje konciznih agenata koji se izvršavaju u specifičnim domenima.</p> / <p>The dissertation presents the prototype of an agent-oriented, domainspecific<br />language ALAS. The basic motives for the development of the<br />ALAS language are support for distributed non-axiomatic reasoning, as well<br />as enabling the interoperability and heterogeneous mobility of agents,<br />because it is concluded by analysing existing agent-oriented, domainspecific<br />languages, that there is no language that supports these<br />requirements. The improvement compared to similar existing agentoriented,<br />domain-specific languages are also reflected in program<br />constructs offered by ALAS language, whose the main purpose is to enable<br />writing the concise agents that are executed in specific domains.</p>

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-05-25T12:29:15Z No. of bitstreams: 1 AutoEduMat.pdf: 1060362 bytes, checksum: 25b8156de4b9c2c2c5b9dc0f69aea011 (MD5) / Made available in DSpace on 2015-05-25T12:29:15Z (GMT). No. of bitstreams: 1 AutoEduMat.pdf: 1060362 bytes, checksum: 25b8156de4b9c2c2c5b9dc0f69aea011 (MD5) Previous issue date: 2010 / Nenhuma / Esta dissertação apresenta uma pesquisa relacionada as ferramentas que dão suporte a utilização de objetos de aprendizagem em plataformas digitais. Mais especificamente, a pesquisa se direciona para as ferramentas de apoio a autoria destes objetos, em particular dos seus metadados. Inicialmente é apresentada a contextualização do problema de pesquisa, sua fundamentação teórica e os trabalhos relacionados ao tema. Em seguida são apresentadas as principais características do sistema proposto, o AutoEduMat - Ferramenta de Apoio a Autoria de Metadados de Objetos de Aprendizagem para o Domínio de Ensino de Matemática. A ferramenta AutoEduMat dá apoio a autoria de objetos de aprendizagem, oferecendo assistência ao projetista (designer) de objetos na criação e edição de metadados destes objetos. A principal inovação do trabalho é a combinação das tecnologias de Engenharia de Software de Agentes e de Engenharia de Ontologias para construir um sistema multiagente que oferece suporte inteligente para a geração dos metadados dos objetos de aprendizagem, sendo capaz de interagir com o usuário com termos de seu próprio contexto profissional e educacional. No trabalho é proposta a ontologia Onto-EduMat que incorpora os conhecimentos sobre o domínio de ensino de matemática, incluindo aspectos pedagógicos, necessários para o auxílio a geração dos metadados. Tanto a ferramenta quanto seu modelo ontológico são validados através de experimentos descritos no final do trabalho. / This dissertation presents a research related to the tools that support the utilization of learning objects in digital platforms. More precisely, the research is directed to the tools that support the authoring process of these objects, in particular of their metadata. Initially are presented the characterization of the problem, its theoretical foundations and related works. Then are presented the main characteristics of the proposed system, the AutoEduMat - Metadata Authoring Tool for Mathematics Learning Objects. The AutoEduMat system will provide assistance to the object designer in the metadata creation and edition of these objects. The main innovation of this work is the combination of Agent Oriented Software Engineering and Ontology Engineering technologies to built a multiagent system able to offer intelligent support for metadata creation, interacting with users using terms related to their professional and educational context. This work proposes the Onto-EduMat ontology, which incorporates the mathematical and pedagogical knowledge necessary to generate the metadata. The authoring tool and its ontological model are validated through experiments described in the end of the work.