Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-10-17T17:58:28Z No. of bitstreams: 2 Dissertação - Alison Carlos Filgueiras - 2013.pdf: 3916567 bytes, checksum: 312992aa8f3f3d2a95d036654378912e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2014-10-17T20:31:36Z (GMT) No. of bitstreams: 2 Dissertação - Alison Carlos Filgueiras - 2013.pdf: 3916567 bytes, checksum: 312992aa8f3f3d2a95d036654378912e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-10-17T20:31:36Z (GMT). No. of bitstreams: 2 Dissertação - Alison Carlos Filgueiras - 2013.pdf: 3916567 bytes, checksum: 312992aa8f3f3d2a95d036654378912e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-07-29 / Context: keyword research is a highly used feature for retrieval of information through the search engines available on the Internet. Much of the information in the world, however, is not achieved by conventional search to be stored in databases, relational most. The integrated search information from di erent data sources is explored by several studies, still, no studies were found to bring e ective solutions when it includes, among these data sources, relational databases. Objective: The emphasis of this study is to present a solution for retrieval of information stored in heterogeneous data sources using the OAI-PMH as a mechanism to enable interoperability. Method: Implementing a system that runs queries for keywords in heterogeneous data sources from the collection of metadata exposed to OAIPMH data providers in. Furthermore, the proposal is for a web service that uses public methods to allow information relational databases are returned without the need for additional e orts, such as knowledge of the structure of the database or use SQL. Results: The simulations produced a return of information from metadata of digital objects and relational databases, obtained from data providers. The query execution examples was successful in retrieving information on all data sources surveyed. Conclusion: This work proposes a solution for information retrieval stored in heterogeneous data sources. The proposed solution was feasible to allow consultation by keywords in digital libraries and relational databases using the OAI-PMH. The proposed web service enabled information relational databases were obtained by external applications, without requiring / Contexto: Consulta com palavras-chave e um recurso altamente utilizado para recupera ção de informa ções atrav és dos motores de busca dispon íveis na Internet. Grande parte da informa ção existente no mundo, no entanto, não e alcan çada pelos processos convencionais de busca por estar armazenada em bancos de dados, na maioria relacionais. A busca integrada de informa ções de diferentes fontes de dados e explorada por diversos trabalhos, entretanto, não foram encontrados estudos que trouxessem solu ções efetivas quando se inclui, dentre essas fontes de dados, bancos de dados relacionais. Objetivo: A ênfase deste estudo e apresentar uma solu ção para recupera ção de informação armazenada em fontes de dados heterogêneas, utilizando o protocolo OAI-PMH como mecanismo para viabilizar interoperabilidade.M étodo: Implementa ção de um sistema que executa consultas por palavras-chave em fontes de dados heterogêneas a partir da coleta de metadados expostos com o protocolo OAI-PMH em provedores de dados. Al ém disso, e apresentada uma proposta de um web service que utiliza m étodos p úblicos para permitir que as informa ções de bancos de dados relacionais sejam retornadas sem a necessidade de esfor ços adicionais, tais como conhecimento da estrutura do banco de dados ou uso de SQL. Resultados: As simula ções produziram o retorno de informa ções a partir de metadados de objetos digitais e bancos de dados relacionais, obtidos a partir de provedores de dados. A execu ção de consultas exemplos foi bem sucedida na recupera ção de informa ções em todas as fontes de dados pesquisadas. Conclusão: Este trabalho apresenta uma proposta de solu ção para recupera ção de informa ção armazenada em fontes de dados heterogêneas. A solu ção proposta mostrou-se vi ável ao permitir a consulta por palavras-chave em bibliotecas digitais e bancos de dados relacionais utilizando o protocolo OAI-PMH. O web service proposto permitiu que informa ções de bancos de dados relacionais fossem obtidas por aplica ções externas, sem que estas necessitem conhecer a estrutura dos bancos de dados consultados ou uma linguagem de consulta como SQL.

Storage, preservation and access of Master's and PhD theses as well as their abstracts in an electronic form provide unique opportunities to the academic community in Lithuania as well as worldwide. The main aims of this project were to establish an archive (Lithuanian ETD IS) of Lithuanian student final year projects, PhD theses and their abstracts in an electronic form (ETD). This archive should become a part of the Lithuanian academic library network (LABT), ensuring registration and storage of ETD documents, and should be accessible by the academic community in Lithuania and the rest of the world. In order to develop the Lithuanian ETD IS, the most widely used formats and methods for access, retrieval and exchange with NDLTD and other national ETD projects were employed. A solution, ensuring efficient ETD registration, preservation, retrieval and access by users, is presented and discussed. Application of the ExLibris programming products (ALEPH500™, MetaLib™, SFX™), developed during the LABT project, was used.

This project presents a Materials Informatics Workbench that resolves the challenges confronting materials scientists in the aspects of materials science data assimilation and dissemination. It adopts an approach that has ingeniously combined and extended the technologies of the Semantic Web, Web Service Business Process Execution Language (WSBPEL) and Open Archive Initiative Object Reuse and Exchange (OAI-ORE). These technologies enable the development of novel user interfaces and innovative algorithms and techniques behind the major components of the proposed workbench. In recent years, materials scientists have been struggling with the challenge of dealing with the ever-increasing amount of complex materials science data that are available from online sources and generated by the high-throughput laboratory instruments and data-intensive software tools, respectively. Meanwhile, the funding organizations have encouraged, and even mandated, the sponsored researchers across many domains to make the scientifically-valuable data, together with the traditional scholarly publications, available to the public. This open access requirement provides the opportunity for materials scientists who are able to exploit the available data to expedite the discovery of novel compound materials. However, it also poses challenges for them. The materials scientists raise concerns about the difficulties of precisely locating and processing diverse, but related, data from different data sources and of effectively managing laboratory information and data. In addition, they also lack the simple tools for data access and publication, and require measures for Intellectual Property protection and standards for data sharing, exchange and reuse. The following paragraphs describe how the major workbench components resolve these challenges. First, the materials science ontology, represented in the Web Ontology Language (OWL), enables, (1) the mapping between and the integration of the disparate materials science databases, (2) the modelling of experimental provenance information acquired in the physical and digital domains and, (3) the inferencing and extraction of new knowledge within the materials science domain. Next, the federated search interface based on the materials science ontology enables the materials scientists to search, retrieve, correlate and integrate diverse, but related, materials science data and information across disparate databases. Then, a workflow management system underpinning the WSBPEL engine is not only able to manage the scientific investigation process that incorporates multidisciplinary scientists distributed over a wide geographic region and self-contained computational services, but also systematically acquire the experimental data and information generated by the process. Finally, the provenance-aware scientific compound-object publishing system provides the scientists with a view of the highly complex scientific workflow at multiple-grained levels. Thus, they can easily comprehend the science of the workflow, access experimental information and keep the confidential information from unauthorised viewers. It also enables the scientists to quickly and easily author and publish a scientific compound object that, (1) incorporates not only the internal experimental data with the provenance information from the rendered view of a scientific experimental workflow, but also external digital objects with the metadata, for example, published scholarly papers discoverable via the World Wide Web (the Web), (2) is self- contained and explanatory with IP protection and, (3) is guaranteed to be disseminated widely on the Web. The prototype systems of the major workbench components have been developed. The quality of the material science ontology has been assessed, based on Gruber’s principles for the design of ontologies used for knowledge–sharing, while its applicability has been evaluated through two of the workbench components, the ontology-based federated search interface and the provenance-aware scientific compound object publishing system. Those prototype systems have been deployed within a team of fuel cell scientists working within the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. Following the user evaluation, the overall feedback to date has been very positive. First, the scientists were impressed with the convenience of the ontology-based federated search interface because of the easy and quick access to the integrated databases and analytical tools. Next, they felt the surge of the relief that the complex compound synthesis process could be managed by and monitored through the WSBPEL workflow management system. They were also excited because the system is able to systematically acquire huge amounts of complex experimental data produced by self-contained computational services that is no longer handled manually with paper-based laboratory notebooks. Finally, the scientific compound object publishing system inspired them to publish their data voluntarily, because it provides them with a scientific-friendly and intuitive interface that enables scientists to, (1) intuitively access experimental data and information, (2) author self-contained and explanatory scientific compound objects that incorporate experimental data and information about research outcomes, and published scholarly papers and peer-reviewed datasets to strengthen those outcomes, (3) enforce proper measures for IP protection, (4) comply those objects with the Open Archives Initiative Protocol – Object Exchange and Reuse (OAI-ORE) to maximize its dissemination over the Web and,(5) ingest those objects into a Fedora-based digital library.

This project presents a Materials Informatics Workbench that resolves the challenges confronting materials scientists in the aspects of materials science data assimilation and dissemination. It adopts an approach that has ingeniously combined and extended the technologies of the Semantic Web, Web Service Business Process Execution Language (WSBPEL) and Open Archive Initiative Object Reuse and Exchange (OAI-ORE). These technologies enable the development of novel user interfaces and innovative algorithms and techniques behind the major components of the proposed workbench. In recent years, materials scientists have been struggling with the challenge of dealing with the ever-increasing amount of complex materials science data that are available from online sources and generated by the high-throughput laboratory instruments and data-intensive software tools, respectively. Meanwhile, the funding organizations have encouraged, and even mandated, the sponsored researchers across many domains to make the scientifically-valuable data, together with the traditional scholarly publications, available to the public. This open access requirement provides the opportunity for materials scientists who are able to exploit the available data to expedite the discovery of novel compound materials. However, it also poses challenges for them. The materials scientists raise concerns about the difficulties of precisely locating and processing diverse, but related, data from different data sources and of effectively managing laboratory information and data. In addition, they also lack the simple tools for data access and publication, and require measures for Intellectual Property protection and standards for data sharing, exchange and reuse. The following paragraphs describe how the major workbench components resolve these challenges. First, the materials science ontology, represented in the Web Ontology Language (OWL), enables, (1) the mapping between and the integration of the disparate materials science databases, (2) the modelling of experimental provenance information acquired in the physical and digital domains and, (3) the inferencing and extraction of new knowledge within the materials science domain. Next, the federated search interface based on the materials science ontology enables the materials scientists to search, retrieve, correlate and integrate diverse, but related, materials science data and information across disparate databases. Then, a workflow management system underpinning the WSBPEL engine is not only able to manage the scientific investigation process that incorporates multidisciplinary scientists distributed over a wide geographic region and self-contained computational services, but also systematically acquire the experimental data and information generated by the process. Finally, the provenance-aware scientific compound-object publishing system provides the scientists with a view of the highly complex scientific workflow at multiple-grained levels. Thus, they can easily comprehend the science of the workflow, access experimental information and keep the confidential information from unauthorised viewers. It also enables the scientists to quickly and easily author and publish a scientific compound object that, (1) incorporates not only the internal experimental data with the provenance information from the rendered view of a scientific experimental workflow, but also external digital objects with the metadata, for example, published scholarly papers discoverable via the World Wide Web (the Web), (2) is self- contained and explanatory with IP protection and, (3) is guaranteed to be disseminated widely on the Web. The prototype systems of the major workbench components have been developed. The quality of the material science ontology has been assessed, based on Gruber’s principles for the design of ontologies used for knowledge–sharing, while its applicability has been evaluated through two of the workbench components, the ontology-based federated search interface and the provenance-aware scientific compound object publishing system. Those prototype systems have been deployed within a team of fuel cell scientists working within the Australian Institute for Bioengineering and Nanotechnology (AIBN) at the University of Queensland. Following the user evaluation, the overall feedback to date has been very positive. First, the scientists were impressed with the convenience of the ontology-based federated search interface because of the easy and quick access to the integrated databases and analytical tools. Next, they felt the surge of the relief that the complex compound synthesis process could be managed by and monitored through the WSBPEL workflow management system. They were also excited because the system is able to systematically acquire huge amounts of complex experimental data produced by self-contained computational services that is no longer handled manually with paper-based laboratory notebooks. Finally, the scientific compound object publishing system inspired them to publish their data voluntarily, because it provides them with a scientific-friendly and intuitive interface that enables scientists to, (1) intuitively access experimental data and information, (2) author self-contained and explanatory scientific compound objects that incorporate experimental data and information about research outcomes, and published scholarly papers and peer-reviewed datasets to strengthen those outcomes, (3) enforce proper measures for IP protection, (4) comply those objects with the Open Archives Initiative Protocol – Object Exchange and Reuse (OAI-ORE) to maximize its dissemination over the Web and,(5) ingest those objects into a Fedora-based digital library.

The dissertation is devoted to analysis of current practice and trends in providing repositories of electronic theses and dissertation (ETDs) in terms of their management, searching and dissemination. The first part presents terminology and the current state of access to ETDs in Czech and foreign repositories and includes results of a survey of the state of access to ETDs in the Czech Republic which was completed in 2014 by all public universities. In the second part, a metadata standard is presented, particularly the possibility of mapping EVSKP-MS metadata elements to other metadata formats and utilization within the OAI-PMH protocol. The issue of access to ETDs is dealt with further in terms of metrics for an evaluation of usage of distributed ETDs. Searching for ETDs is also described in case studies as are recommendations for public tenders for a discovery service and for creating an ETD metadata search server and an associated user interface with faceted search. The final part of the thesis focuses on the issue of plagiarism. This incorporates a presentation and analysis of the most important plagiarism detection systems and a case study of the development of the portal Validátor VŠE to provide access to results of document analysis.

This report explores the integration of 5G cellular networks with Time-Sensitive Networks (TSN), focusing on network latencies. While mobile 5G networks offer high bandwidth and low latency, TSN is an IEEE standard-based wired solution used in real-time applications for deterministic data transmission with low latency and high reliability. Integrating TSN with 5G could significantly enhance scalability, particularly in industrial automation, by providing flexibility, efficiency, and responsiveness. When combining 5G capabilities with TSN, seamless communication across wired and wireless domains becomes achievable. 5G supports several Quality of Service (QoS) flows with different priorities that must map to TSN QoS to ensure smooth integration. To meet TSN's requirements for latency and jitter, effective traffic translation and forwarding between the networks are crucial. This thesis aims to address key questions regarding traffic translation, QoS implementation, and latency in both TSN and 5G networks. Through experiments and evaluations, we assess latency and network capabilities. Understanding these metrics is essential for devising effective integration strategies. Our findings indicate that integrating 5G with TSN is feasible for achieving low latencies for packet sizes below 128-bytes. However, as packet sizes increase, latencies and jitter rise significantly. This result indicates that Firecell 5G technology may have difficulties efficiently handling larger packet sizes without latency degradation. Additionally, leveraging QoS functionalities in the current version of OpenAirInterface (OAI), which forms the foundation of the utilized Firecell 5G, is currently unattainable. This thesis highlights the importance of implementing QoS functionalities to maintain low latencies and jitter in targeted network applications. / Denna rapport undersöker den potentiella integrationen av 5G-mobilnät med tidskänsliga nätverk (TSN), med fokus på nätverksfördröjningar. Medan 5G-nät erbjuder hög bandbredd och låg fördröjning, är TSN en IEEE-standardiserad trådbunden teknik som används i realtidsapplikationer för deterministisk dataöverföring med låg fördröjning och hög tillförlitlighet. Att integrera TSN med 5G kan avsevärt förbättra skalbarheten, särskilt inom industriell automation, genom att erbjuda flexibilitet, effektivitet och låg fördröjning. Genom att kombinera 5G med TSN blir tidskänslig kommunikation över trådbundna och trådlösa nätverk möjligt. 5G stödjer flera kvalitetsnivåer för tjänster (QoS) med olika prioriteringar som måste anpassas till TSN:s QoS för att säkerställa en smidig integration. För att möta TSN:s krav på fördröjning och jitter är effektiv datahantering mellan nätverken avgörande. Denna avhandling behandlar centrala frågor kring datahantering, QoS-implementering och fördröjning i både TSN och 5G-nätverk. Genom experiment och utvärderingar får vi fram information om fördröjning och nätverkskapacitet i TSN-5G, vilket är avgörande för att utveckla effektiva integrationsstrategier. Våra resultat visar att integrationen av TSN-5G uppnår låg fördröjning för paketstorlekar under 128 byte. När paketstorleken ökar, ökar också fördröjning och jitter avsevärt. Resultaten visar att Firecell 5G-teknologin har svårigheter att effektivt hantera större paketstorlekar utan ökad fördröjning. Utöver detta är det för närvarande inte möjligt att använda QoS-funktioner i den nuvarande versionen av OpenAirInterface (OAI), vilket är mjukvaran Firecell 5G bygger på. Denna avhandling understryker vikten av att kunna implementera QoS-funktioner för att upprätthålla låg fördröjning och jitter i specifika nätverksapplikationer.

Atualmente, pesquisadores e acadêmicos têm beneficiado-se muito com o crescimento acelerado das tecnologias Web, pois os resultados de pesquisa podem ser publicados e acessados eletronicamente tão logo a mesma tenha sido realizada. Esta possibilidade é vantajosa na medida em que minimiza as barreiras de tempo e espaço associadas à publicação tradicional. Neste contexto, surgem as Bibliotecas Digitais como repositórios de dados que, além dos documentos digitais propriamente ditos, ou de apontadores para estes documentos, armazenam os metadados associados. Para permitir que diferentes Bibliotecas Digitais possam interoperar surgiu a Open Archives Initiative (OAI) e, para resolver a questão da padronização dos metadados utilizados pelos repositórios, foi criado o formato Dublin Core (DC). Por outro lado, a enorme quantidade de documentos digitais disponíveis na Web tem causado o fenômeno conhecido como “sobrecarga de informação”. Com o objetivo de suprir esta dificuldade, Sistemas de Recomendação têm sido propostos e desenvolvidos. Estes sistemas visam prover uma interface alternativa para tecnologias de filtragem e recuperação de informações, tendo como foco a predição daqueles itens ou partes da informação que o usuário acharia interessante e útil. Portanto, os Sistemas de Recomendação atuam baseados em personalização da informação sendo que as predições geralmente são realizadas utilizando-se um perfil de cada usuário. A personalização está relacionada com o modo pelo qual a informação e serviços podem ser ajustados às necessidades específicas de um usuário ou comunidade. Esta dissertação descreve um Sistema de Recomendação de artigos científicos, armazenados em bibliotecas digitais. Este sistema é dirigido à comunidade científica da área da Ciência da Computação. Tecnologicamente, o sistema proposto foi desenvolvido sob a perspectiva da Web Semântica, à medida que faz uso de suas tecnologias emergentes tais como: uso de metadados padrão para a descrição de documentos - Dublin Core, uso do padrão XML para a descrição do perfil do usuário - Currículo Lattes, e provedores de serviços e de dados (OAI) envolvidos no processo de geração das recomendações. Este trabalho ainda apresenta e discute alguns resultados de experimentos baseados em avaliações quantitativas e qualitativas de recomendações geradas pelo sistema. / Currently, researchers and academics have been benefited by the expressive growth of web technologies, due to the possibility of publishing and accessing research results as soon as they are achieved. This possibility is advantageous as it minimizes the time and space barriers that traditional publications present. In this context, Digital Libraries emerged as data repositories that, beyond digital documents or links to them, store associated metadata. To allow the interoperability among different Digital Libraries, the Open Archives Initiative (OAI) was defined and, to solve the problem of metadata standardization, the Dublin Core standard (DC) was created. On the other hand, the great amount of available digital documents in the Web has caused the phenomenon known as “information overload”. In order to avoid this difficulty, Recommender Systems have been proposed and developed. These systems intend to provide an alternative interface for information filtering and retrieval technologies, focusing on the prediction of items or information parts that are interesting and useful for the user. Therefore, Recommender Systems act based on information personalization, and the predictions are generally generated using each user’s profile. The personalization is related to the way the information and the provided services can be adjusted to the specific necessities of a user or community. This dissertation describes a Recommender System for scientific articles stored in digital libraries. This system is geared towards the Computer Science scientific community. Technologically, the proposed system was developed under the Semantic Web perspective, as it explores its emergent technologies such as: use of standard metadata for document description - Dublin Core, use of the XML standard for users’ profile description - Lattes Curriculum Vitae, and services and data providers (OAI) involved on the recommendations generation process. In addition, this work presents and discusses some experimental results; the experiments are based on quantitative and qualitative evaluations of recommendations generated by the system.

Atualmente, pesquisadores e acadêmicos têm beneficiado-se muito com o crescimento acelerado das tecnologias Web, pois os resultados de pesquisa podem ser publicados e acessados eletronicamente tão logo a mesma tenha sido realizada. Esta possibilidade é vantajosa na medida em que minimiza as barreiras de tempo e espaço associadas à publicação tradicional. Neste contexto, surgem as Bibliotecas Digitais como repositórios de dados que, além dos documentos digitais propriamente ditos, ou de apontadores para estes documentos, armazenam os metadados associados. Para permitir que diferentes Bibliotecas Digitais possam interoperar surgiu a Open Archives Initiative (OAI) e, para resolver a questão da padronização dos metadados utilizados pelos repositórios, foi criado o formato Dublin Core (DC). Por outro lado, a enorme quantidade de documentos digitais disponíveis na Web tem causado o fenômeno conhecido como “sobrecarga de informação”. Com o objetivo de suprir esta dificuldade, Sistemas de Recomendação têm sido propostos e desenvolvidos. Estes sistemas visam prover uma interface alternativa para tecnologias de filtragem e recuperação de informações, tendo como foco a predição daqueles itens ou partes da informação que o usuário acharia interessante e útil. Portanto, os Sistemas de Recomendação atuam baseados em personalização da informação sendo que as predições geralmente são realizadas utilizando-se um perfil de cada usuário. A personalização está relacionada com o modo pelo qual a informação e serviços podem ser ajustados às necessidades específicas de um usuário ou comunidade. Esta dissertação descreve um Sistema de Recomendação de artigos científicos, armazenados em bibliotecas digitais. Este sistema é dirigido à comunidade científica da área da Ciência da Computação. Tecnologicamente, o sistema proposto foi desenvolvido sob a perspectiva da Web Semântica, à medida que faz uso de suas tecnologias emergentes tais como: uso de metadados padrão para a descrição de documentos - Dublin Core, uso do padrão XML para a descrição do perfil do usuário - Currículo Lattes, e provedores de serviços e de dados (OAI) envolvidos no processo de geração das recomendações. Este trabalho ainda apresenta e discute alguns resultados de experimentos baseados em avaliações quantitativas e qualitativas de recomendações geradas pelo sistema. / Currently, researchers and academics have been benefited by the expressive growth of web technologies, due to the possibility of publishing and accessing research results as soon as they are achieved. This possibility is advantageous as it minimizes the time and space barriers that traditional publications present. In this context, Digital Libraries emerged as data repositories that, beyond digital documents or links to them, store associated metadata. To allow the interoperability among different Digital Libraries, the Open Archives Initiative (OAI) was defined and, to solve the problem of metadata standardization, the Dublin Core standard (DC) was created. On the other hand, the great amount of available digital documents in the Web has caused the phenomenon known as “information overload”. In order to avoid this difficulty, Recommender Systems have been proposed and developed. These systems intend to provide an alternative interface for information filtering and retrieval technologies, focusing on the prediction of items or information parts that are interesting and useful for the user. Therefore, Recommender Systems act based on information personalization, and the predictions are generally generated using each user’s profile. The personalization is related to the way the information and the provided services can be adjusted to the specific necessities of a user or community. This dissertation describes a Recommender System for scientific articles stored in digital libraries. This system is geared towards the Computer Science scientific community. Technologically, the proposed system was developed under the Semantic Web perspective, as it explores its emergent technologies such as: use of standard metadata for document description - Dublin Core, use of the XML standard for users’ profile description - Lattes Curriculum Vitae, and services and data providers (OAI) involved on the recommendations generation process. In addition, this work presents and discusses some experimental results; the experiments are based on quantitative and qualitative evaluations of recommendations generated by the system.

Atualmente, pesquisadores e acadêmicos têm beneficiado-se muito com o crescimento acelerado das tecnologias Web, pois os resultados de pesquisa podem ser publicados e acessados eletronicamente tão logo a mesma tenha sido realizada. Esta possibilidade é vantajosa na medida em que minimiza as barreiras de tempo e espaço associadas à publicação tradicional. Neste contexto, surgem as Bibliotecas Digitais como repositórios de dados que, além dos documentos digitais propriamente ditos, ou de apontadores para estes documentos, armazenam os metadados associados. Para permitir que diferentes Bibliotecas Digitais possam interoperar surgiu a Open Archives Initiative (OAI) e, para resolver a questão da padronização dos metadados utilizados pelos repositórios, foi criado o formato Dublin Core (DC). Por outro lado, a enorme quantidade de documentos digitais disponíveis na Web tem causado o fenômeno conhecido como “sobrecarga de informação”. Com o objetivo de suprir esta dificuldade, Sistemas de Recomendação têm sido propostos e desenvolvidos. Estes sistemas visam prover uma interface alternativa para tecnologias de filtragem e recuperação de informações, tendo como foco a predição daqueles itens ou partes da informação que o usuário acharia interessante e útil. Portanto, os Sistemas de Recomendação atuam baseados em personalização da informação sendo que as predições geralmente são realizadas utilizando-se um perfil de cada usuário. A personalização está relacionada com o modo pelo qual a informação e serviços podem ser ajustados às necessidades específicas de um usuário ou comunidade. Esta dissertação descreve um Sistema de Recomendação de artigos científicos, armazenados em bibliotecas digitais. Este sistema é dirigido à comunidade científica da área da Ciência da Computação. Tecnologicamente, o sistema proposto foi desenvolvido sob a perspectiva da Web Semântica, à medida que faz uso de suas tecnologias emergentes tais como: uso de metadados padrão para a descrição de documentos - Dublin Core, uso do padrão XML para a descrição do perfil do usuário - Currículo Lattes, e provedores de serviços e de dados (OAI) envolvidos no processo de geração das recomendações. Este trabalho ainda apresenta e discute alguns resultados de experimentos baseados em avaliações quantitativas e qualitativas de recomendações geradas pelo sistema. / Currently, researchers and academics have been benefited by the expressive growth of web technologies, due to the possibility of publishing and accessing research results as soon as they are achieved. This possibility is advantageous as it minimizes the time and space barriers that traditional publications present. In this context, Digital Libraries emerged as data repositories that, beyond digital documents or links to them, store associated metadata. To allow the interoperability among different Digital Libraries, the Open Archives Initiative (OAI) was defined and, to solve the problem of metadata standardization, the Dublin Core standard (DC) was created. On the other hand, the great amount of available digital documents in the Web has caused the phenomenon known as “information overload”. In order to avoid this difficulty, Recommender Systems have been proposed and developed. These systems intend to provide an alternative interface for information filtering and retrieval technologies, focusing on the prediction of items or information parts that are interesting and useful for the user. Therefore, Recommender Systems act based on information personalization, and the predictions are generally generated using each user’s profile. The personalization is related to the way the information and the provided services can be adjusted to the specific necessities of a user or community. This dissertation describes a Recommender System for scientific articles stored in digital libraries. This system is geared towards the Computer Science scientific community. Technologically, the proposed system was developed under the Semantic Web perspective, as it explores its emergent technologies such as: use of standard metadata for document description - Dublin Core, use of the XML standard for users’ profile description - Lattes Curriculum Vitae, and services and data providers (OAI) involved on the recommendations generation process. In addition, this work presents and discusses some experimental results; the experiments are based on quantitative and qualitative evaluations of recommendations generated by the system.

Made available in DSpace on 2014-07-29T14:57:53Z (GMT). No. of bitstreams: 1 Renan Rodrigues 1.pdf: 1818012 bytes, checksum: b12a88acdfeb11f473ab5b1087c11311 (MD5) Previous issue date: 2010-04-09 / This work focuses on two aspects: the integration of a set of digital libraries, repositories and other data providers through the OAI-PMH protocol (Open Archives Initiative Protocol for Metadata Harvesting) and contextualized documents retrieval in this integrated repository. It is proposed the use of ontologies and content analysis of articles in wiki environments in the context definition. The interest in ontologies is in its use as artifacts of specification domain. An ontology is a data model that represents a set of concepts and their relationships within a domain of knowledge. A wiki is a collaborative environment, containing a collection of items connected by hyperlinks, which can be edited collectively by using a web browser. In this work, the wiki environments are used as an auxiliary repository of knowledge to the extraction of relevant terms. Thus, several concepts and relationships that may not be present in the ontology that specifies the domain of knowledge (since the construction of ontologies is a complex process) can be identified. The result of the developed tool processing is a ranking of documents ordered by a higher degree of importance with respect to the query provided by a user and a particular domain of knowledge, which is specified by an ontology. / Este trabalho aborda duas vertentes: a integração de um conjunto de bibliotecas digitais, repositórios e outros provedores de dados por meio do protocolo OAI-PMH (Open Archives Initiative Protocol for Metadata Harvesting) e a recuperação contextualizada de documentos neste repositório integrado. Propõe-se a definição dos contextos utilizando ontologias e a análise do conteúdo de artigos de ambientes wiki. O interesse em ontologias está no seu uso como artefatos de especificação de domínios. Uma ontologia é um modelo de dados que representa um conjunto de conceitos e seus relacionamentos, dentro de um domínio de conhecimento. Um wiki é um ambiente colaborativo, que contêm uma coleção de artigos conectados através de hiperlinks, que podem ser editados coletivamente, através da utilização de um navegador web. Neste trabalho, os ambientes wiki são utilizados como um repositório de conhecimento auxiliar, para a extração de termos relevantes. Dessa forma, diversos conceitos e relacionamentos que podem não estar presentes na ontologia que especifica o domínio de conhecimento (uma vez que a construção de ontologias é um processo complexo) podem ser identificados. O resultado do processamento da ferramenta desenvolvida é um ranking de documentos ordenado por maior grau de relevância com relação à consulta fornecida por um usuário e a um determinado domínio de conhecimento, que é especificado por uma ontologia.