In multimedia databases, data are images, audio, video, texts, etc. Research interests in these types of databases have increased in the last decade or so, especially with the advent of the Internet and Semantic Web. Fundamental research issues vary from unified data modelling, retrieval of data items and dynamic nature of updates. The thesis builds on findings in Semantic Web and retrieval techniques and explores novel tagging methods for identifying data items. Tagging systems have become popular which enable the users to add tags to Internet resources such as images, video and audio to make them more manageable. Collaborative tagging is concerned with the relationship between people and resources. Most of these resources have metadata in machine processable format and enable users to use free- text keywords (so-called tags) as search techniques. This research references some tagging systems, e.g. Flicker, delicious and myweb2.0. The limitation with such techniques includes polysemy (one word and different meaning), synonymy (different words and one meaning), different lexical forms (singular, plural, and conjugated words) and misspelling errors or alternate spellings. The work presented in this thesis introduces semantic characterization of web resources that describes the structure and organization of tagging, aiming to extend the existing Multimedia Query using similarity measures to cater for collaborative tagging. In addition, we discuss the semantic difficulties of tagging systems, suggesting improvements in their accuracies. The scope of our work is classified as follows: (i) Increase the accuracy and confidence of multimedia tagging systems. (ii) Increase the similarity measures of images by integrating varieties of measures. To address the first shortcoming, we use the WordNet based on a tagging system for social sharing and retrieval of images as a semantic lingual ontology resource. For the second shortcoming we use the similarity measures in different ways to recognise the multimedia tagging system. Fundamental to our work is the novel information model that we have constructed for our computation. This is based on the fact that an image is a rich object that can be characterised and formulated in n-dimensions, each dimension contains valuable information that will help in increasing the accuracy of the search. For example an image of a tree in a forest contains more information than an image of the same tree but in a different environment. In this thesis we characterise a data item (an image) by a primary description, followed by n-secondary descriptions. As n increases, the accuracy of the search improves. We give various techniques to analyse data and its associated query. To increase the accuracy of the tagging system we have performed different experiments on many images using similarity measures and various techniques from VoI (Value of Information). The findings have shown the linkage/integration between similarity measures and that VoI improves searches and helps/guides a tagger in choosing the most adequate of tags.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / It is anticipated that XML will heavily dominate the next generation of telemetry systems. The syntax of XML-based languages can be constrained by a schema that describes the structure of valid documents. However, the schemas cannot express all dependencies between XML elements and attributes, both within a single document and across multiple documents. This prohibits the XML validation process from being fully automated with standard schema processors. This paper presents an approach that is based on the W3C Semantic Web technologies and allows different vendors and system integrators to independently develop their own semantic validation rules. The rules are equipped with powerful semantics, which allows for specification and validation of complex types of constraints. The approach is not specific to a particular T&E standard and is entirely standards-based.

The Social Web or ‘Web 2.0’ is focused on the interaction and collaboration between web sites users. It is credited for the existence of tagging systems, amongst other things such as blogs and Wikis. Tagging systems like YouTube and Flickr offer their users the simplicity and freedom in creating and sharing their own contents and thus folksonomy is a very active research area where many improvements are presented to overcome existing disadvantages such as the lack of semantic meaning, ambiguity, and inconsistency. TE is a tagging system proposing solutions to the problems of multilingualism, lack of semantic meaning and shorthand writing (which is very common in the social web) through the aid of semantic and social resources. The current research is presenting an addition to the TE system in the form of an embedded stemming component to provide a solution to the different lexical form problems. Prior to this, the TE system had to be explored thoroughly and then its efficiency had to be determined in order to decide on the practicality of embedding any additional components as enhancements to the performance. Deciding on this involved analysing the algorithm efficiency using an analytical approach to determine its time and space complexity. The TE had a time growth rate of O (N²) which is polynomial, thus the algorithm is considered efficient. Nonetheless, recommended modifications like patch SQL execution can improve this. Regarding space complexity, the number of tags per photo represents the problem size which, if it grows, will increase linearly the required memory space. Based on the findings above, the TE system is re-implemented on Flickr instead of YouTube, because of a recent YouTube restriction, which is of greater benefit in multi languages tagging system since the language barrier is meaningless in this case. The re-implementation is achieved using ‘flickrj’ (Java Interface for Flickr APIs). Next, the stemming component is added to perform tags normalisation prior to the ontologies querying. The component is embedded using the Java encoding of the porter 2 stemmer which support many languages including Italian. The impact of the stemming component on the performance of the TE system in terms of the size of the index table and the number of retrieved results is investigated using an experiment that showed a reduction of 48% in the size of the index table. This also means that search queries have less system tags to compare them against the search keywords and this can speed up the search. Furthermore, the experiment runs similar search trails on two versions of the TE systems one without the stemming component and the other with the stemming component and found out that the latter produced more results on the conditions of working with valid words and valid stems. The embedding of the stemming component in the new TE system has lessened the effect of the storage overhead needed for the generated system tags by their reduction for the size of the index table which make the system suited for many applications such as text classification, summarization, email filtering, machine translation…etc.

With the emergence of the Internet and of the World Wide Web, the Web site has become a key communication channel in organizations. To satisfy the objectives of the Web site and of its target audience, adapting the Web site content to the users' expectations has become a major concern. In this context, Web usage mining, a relatively new research area, and Web analytics, a part of Web usage mining that has most emerged in the corporate world, offer many Web communication analysis techniques. These techniques include prediction of the user's behaviour within the site, comparison between expected and actual Web site usage, adjustment of the Web site with respect to the users' interests, and mining and analyzing Web usage data to discover interesting metrics and usage patterns. However, Web usage mining and Web analytics suffer from significant drawbacks when it comes to support the decision-making process at the higher levels in the organization. Indeed, according to organizations theory, the higher levels in the organizations need summarized and conceptual information to take fast, high-level, and effective decisions. For Web sites, these levels include the organization managers and the Web site chief editors. At these levels, the results produced by Web analytics tools are mostly useless. Indeed, most of these results target Web designers and Web developers. Summary reports like the number of visitors and the number of page views can be of some interest to the organization manager but these results are poor. Finally, page-group and directory hits give the Web site chief editor conceptual results, but these are limited by several problems like page synonymy (several pages contain the same topic), page polysemy (a page contains several topics), page temporality, and page volatility. Web usage mining research projects on their part have mostly left aside Web analytics and its limitations and have focused on other research paths. Examples of these paths are usage pattern analysis, personalization, system improvement, site structure modification, marketing business intelligence, and usage characterization. A potential contribution to Web analytics can be found in research about reverse clustering analysis, a technique based on self-organizing feature maps. This technique integrates Web usage mining and Web content mining in order to rank the Web site pages according to an original popularity score. However, the algorithm is not scalable and does not answer the page-polysemy, page-synonymy, page-temporality, and page-volatility problems. As a consequence, these approaches fail at delivering summarized and conceptual results. An interesting attempt to obtain such results has been the Information Scent algorithm, which produces a list of term vectors representing the visitors' needs. These vectors provide a semantic representation of the visitors' needs and can be easily interpreted. Unfortunately, the results suffer from term polysemy and term synonymy, are visit-centric rather than site-centric, and are not scalable to produce. Finally, according to a recent survey, no Web usage mining research project has proposed a satisfying solution to provide site-wide summarized and conceptual audience metrics. In this dissertation, we present our solution to answer the need for summarized and conceptual audience metrics in Web analytics. We first described several methods for mining the Web pages output by Web servers. These methods include content journaling, script parsing, server monitoring, network monitoring, and client-side mining. These techniques can be used alone or in combination to mine the Web pages output by any Web site. Then, the occurrences of taxonomy terms in these pages can be aggregated to provide concept-based audience metrics. To evaluate the results, we implement a prototype and run a number of test cases with real Web sites. According to the first experiments with our prototype and SQL Server OLAP Analysis Service, concept-based metrics prove extremely summarized and much more intuitive than page-based metrics. As a consequence, concept-based metrics can be exploited at higher levels in the organization. For example, organization managers can redefine the organization strategy according to the visitors' interests. Concept-based metrics also give an intuitive view of the messages delivered through the Web site and allow to adapt the Web site communication to the organization objectives. The Web site chief editor on his part can interpret the metrics to redefine the publishing orders and redefine the sub-editors' writing tasks. As decisions at higher levels in the organization should be more effective, concept-based metrics should significantly contribute to Web usage mining and Web analytics.

The Semantic Web project has introduced new techniques for managing information. Data can now be organised more efficiently and in such a way that computers can take advantage of the relationships that characterise the given input to present more relevant output. Semantic Web based search engines can quickly educe exactly what is needed to be found and retrieve it while avoiding information overload. Up until now, search engines have interacted with their users by asking them to look for words and phrases. We propose the creation of a new generation Semantic Web search engine that will offer a visual interface for queries and results. To create such an engine, information input must be viewed not merely as keywords, but as specific concepts and objects which are all part of the same universal system. To make the manipulation of the interconnected visual objects simpler and more natural, 3D graphics are utilised, based on the X3D Web standard, allowing users to semantically synthesise their queries faster and in a more logical way, both for them and the computer.

Accurate situational assessment is key to any decision maker and especially crucial in military command and control, air traffic control, and complex system decision making. Endsley described three dependent levels of situational awareness, (1) perception, (2) understanding, and (3) projection. This research was focused on Endsley's second-level situational awareness (understanding) as it applies to service-oriented information technology environments in the context of the Semantic Web. Specifically, this research addressed the problem of developing accurate situational assessments related to the status or health of information technology (IT) services, especially composite, dynamic IT services, when some of Endsley's first level (perceived) information was inaccurate or incomplete. Research had not adequately addressed the problem of how to work with inaccuracy and situational awareness information in order to produce accurate situational assessments for Semantic Web services. This problem becomes especially important as the current Web moves towards a Semantic Web where information technology is expected to be represented and processed by machines. Costa's probabilistic Web ontology language (PR-OWL), as extended by Carvalho (PR-OWL2), is a framework for storage of and reasoning with uncertainty information as part of the Semantic Web. This study used Costa's PR-OWL framework, as extended by Carvalho, to build an ontology that supports reasoning with service-oriented information in the context of the Semantic Web and then assessed the effectiveness of the developed ontology through the use of competency questions, as described by Gruninger and Fox and verified through the use of an automated reasoner. This research resulted in a Web Ontology Language for Services (OWL-S), PR-OWL2 based ontology, and its associated Multi-Entity Bayesian Network which are flexible and highly effective in calculating situational assessments through the propagation of posterior probabilities using Bayesian logic. Specifically, this research (1) identifies sufficient information required for effective situational awareness reasoning, (2) specifies the predicates and semantics necessary to represent service components and dependencies, (3) applies Multi-Entity Bayesian Network to reason with situational awareness information, (4) ensures the correctness and consistency of the situational awareness ontology, and (5) accurately estimates posterior probabilities consistent with situational awareness information.

The more enhanced and reliable healthcare facilities, depend partly on accumulated organizational knowledge. Ontology and semantic web are the key factors in long-term sustainability towards the improvement of patient treatment process. Generally, researchers have the common consensus that knowledge is hard to capture due to its implicit nature, making it hard to manage. Medical professionals spend more time on getting the right information at the right moment, which is already available on intranet/internet. Evaluating the literature is controversial but interesting debates on ontology and semantic web encouraged us to propose a method and 4-Tier Architecture for retrieving context-based document according to user’s information in healthcare organization. Medical professionals are facing problems to access relevant information and documents for performing different tasks in the patient-treatment process. We have focused to provide context-based retrieval of documents for medical professionals by developing a semantic web solution. We also developed different OWL ontology models, which are mainly used for semantic tagging in web pages and generating context to retrieve the relevant web page documents. In addition, we developed a prototype to testify our findings in health care sector with the goal of retrieving relevant documents in a practical manner. / E-Health

Orientador: José Eduardo Santarem Segundo / Banca: Ricardo César Gonçalves Sant'Ana / Banca: Mário Furlaneto Neto / Resumo: O desenvolvimento da Internet transformou o mundo virtual em um repositório infindável de informações. Diariamente, na sociedade da informação, pessoas interagem, capturam e despejam dados nas mais diversas ferramentas de redes sociais e ambientes da Web. Estamos diante do Big Data, uma quantidade inacabável de dados com valor inestimável, porém de difícil tratamento. Não se tem dimensão da quantidade de informação capaz de ser extraída destes grandes repositórios de dados na Web. Um dos grandes desafios atuais na Internet do "Big Data" é lidar com falsidades e perfis falsos em ferramentas sociais, que causam alardes, comoções e danos financeiros significativos em todo o mundo. A inteligência cibernética e computação forense objetivam investigar eventos e constatar informações extraindo dados da rede. Por sua vez, a Ciência da Informação, preocupada com as questões envolvendo a recuperação, tratamento, interpretação e apresentação da informação, dispõe de elementos que quando aplicados neste contexto podem aprimorar processos de coleta e tratamento de grandes volumes de dados, na detecção de perfis falsos. Assim, por meio da presente pesquisa de revisão de literatura, documental e exploratória, buscou-se revisar os estudos internacionais envolvendo a detecção de perfis falsos em redes sociais, investigando técnicas e tecnologias aplicadas e principalmente, suas limitações. Igualmente, apresenta-se no presente trabalho contribuições de áreas da Ciência da Informação e critério... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The development of the Internet changed the virtual world in an endless repository of information. Every single day, in an information-society, people change, catch and turn out files in different tools of social network and Web surrounding. We are in front of "The Big Data", an endless amount of data with invaluable, but hard treating. It doesn't have some dimension of measure information to be able of extracting from these big Web data repositories. One of the most challenges nowadays on the Internet from the "Big Data" is to identify feelings, anticipating sceneries dealing with falsehood and false profiles social tools, which cause fanfare, upheavals and significant financial losses worldwide in front of our true scene. The cyber intelligence has by objective to look for events and finding information, subtracting dates from the Web. On the other hand, the Information Science, worried with the questions involving recovery, processing, interpretation and presentation of information that has important areas of study capable of being applied in this context hone the collection and treatment processes of large volumes of information (datas). Thus, through this research literature review, documentary and exploratory, the researcher aimed to review the International studies implicating the analysis of large volumes of data on social networking tools in falsehoods detection, investigating applied techniques and technologies and especially their limitations. Based on the identifi... (Complete abstract click electronic access below) / Mestre

Atualmente uma grande quantidade de conteúdo é produzida e publicada todos os dias na Internet. São documentos publicados por diferentes pessoas, por diversas organizações e em inúmeros formatos sem qualquer tipo de padronização. Por esse motivo, a informação relevante sobre um mesmo domínio de interesse acaba espalhada pela Web nos diversos portais, o que dificulta uma visão ampla, centralizada e objetiva sobre esta informação. Nesse contexto, a integração dos dados espalhados na rede torna-se um problema de pesquisa relevante, para permitir a realização de consultas mais inteligentes, de modo a obter resultados mais ricos de significado e mais próximos do interesse do usuário. No entanto, tal integração não é trivial, sendo por muitas vezes custosa devido à dependência do desenvolvimento de sistemas e mão de obra especializados, visto que são poucos os modelos reaproveitáveis e facilmente integráveis entre si. Assim, a existência de um modelo padronizado para a integração dos dados e para o acesso à informação produzida por essas diferentes entidades reduz o esforço na construção de sistemas específicos. Neste trabalho é proposta uma arquitetura baseada em ontologias para a integração de dados publicados na Internet. O seu uso é ilustrado através de casos de uso reais para a integração da informação na Internet, evidenciando como o uso de ontologias pode trazer resultados mais relevantes. / A lot of content is produced and published every day on the Internet. Those documents are published by different people, organizations and in many formats without any type of established standards. For this reason, relevant information about a domain of interest is spread through the Web in various portals, which hinders a broad, centralized and objective view of this information. In this context, the integration of the data scattered in the network becomes a relevant research problem, to enable smarter queries, in order to obtain richer results of meaning and closer to the user\'s interest. However, such integration is not trivial, and is often costly because of the reliance on the development of specialized systems by professionals, since there are few reusable and easily integrable models. Thus, the existence of a standardized model for data integration and access to the information produced by these different entities reduces the effort in the construction of specific systems. In this work we propose an architecture based on ontologies for the integration of data published on the Internet. Its use is illustrated through experimental cases for the integration of information on the Internet, showing how the use of ontologies can bring more relevant results.

Atualmente, existem muitos estudos para agregar mais valor às informações disponíveis na Web visando melhorar os resultados da interação dos usuários com a Web; uma das linhas de estudo é a Web Semântica, que propõe a adição de informação semântica à Web atual por meio de ontologias. A organização internacional que define os padrões para a Web (W3C) já propôs vários padrões para tornar a Web Semântica viável, porém, além de padrões, também é preciso criar ou adaptar ferramentas que explorem as suas potencialidades. Uma ferramenta que dá um suporte significativo para a Web atual e que pode ser adaptada para trabalhar com a Web Semântica é o Servidor de Aplicações. Com adição de informações semânticas, na forma de ontologias, tem-se um Servidor de Aplicações Baseado em Ontologias (OBAS). Neste trabalho foi desenvolvido um sistema protótipo para oferecer as características mínimas de um OBAS, e desta forma, foram investigadas as tecnologias para a Web Semântica que viabilizassem uma solução de acordo com os padrões recomendados pela W3C. Os componentes de software de um OBAS têm suas propriedades e comportamentos relacionados de forma semântica usando-se ontologias. Como uma ontologia é um modelo conceitual explícito, suas descrições dos componentes podem ser consultadas e inferidas, melhorando o desempenho do servidor através da combinação dos componentes mais apropriados a uma tarefa, da simplificação da programação, pois não é mais necessário saber todos os detalhes de um componente para ativá-lo / Many studies have been carried out to add more value to the available information in the Web with a view to improving the results of the users\' interaction with the Web. Semantic Web is one line of research with focus on this issue and proposes the insertion of semantic information to the current Web through ontologies. Several patterns have been proposed by W3C, the international organization that defines patterns to the Web as an attempt to make the Semantic Web viable. However, besides patterns, it is also necessary to create or adapt tools to explore their potentialities. Application Server is a tool which gives significant support to the current Web and could be adapted to work with the Semantic Web. By adding semantic information, in the ontology form, we have an Ontology-Based Application Server (OBAS). This study develops a protoptype system which aims to offer the minimum characteristics of an OBAS. We have therefore investigated the semantic web which could provide a solution according to the patterns recommended by W3C. Properties and behaviors of software components of OBAS are semantically related by means of ontologies. Given that ontology is an explicit conceptual model, its component descriptions can be consulted and inferred, and hence improve the performance of the server. This is done by applying the most appropriate components to a given task and simplifying programming since components can be activated with no need to know all their details