871 resultados para semi-structured interviews


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A Teia Mundial (Web) foi prevista como uma rede de documentos de hipertexto interligados de forma a criar uma espaço de informação onde humanos e máquinas poderiam comunicar. No entanto, a informação contida na Web tradicional foi/é armazenada de forma não estruturada o que leva a que apenas os humanos a possam consumir convenientemente. Consequentemente, a procura de informações na Web sintáctica é uma tarefa principalmente executada pelos humanos e nesse sentido nem sempre é fácil de concretizar. Neste contexto, tornou-se essencial a evolução para uma Web mais estruturada e mais significativa onde é dado significado bem definido à informação de forma a permitir a cooperação entre humanos e máquinas. Esta Web é usualmente referida como Web Semântica. Além disso, a Web Semântica é totalmente alcançável apenas se os dados de diferentes fontes forem ligados criando assim um repositório de Dados Abertos Ligados (LOD). Com o aparecimento de uma nova Web de Dados (Abertos) Ligados (i.e. a Web Semântica), novas oportunidades e desafios surgiram. Pergunta Resposta (QA) sobre informação semântica é actualmente uma área de investigação activa que tenta tirar vantagens do uso das tecnologias ligadas à Web Semântica para melhorar a tarefa de responder a questões. O principal objectivo do projecto World Search passa por explorar a Web Semântica para criar mecanismos que suportem os utilizadores de domínios de aplicação específicos a responder a questões complexas com base em dados oriundos de diferentes repositórios. No entanto, a avaliação feita ao estado da arte permite concluir que as aplicações existentes não suportam os utilizadores na resposta a questões complexas. Nesse sentido, o trabalho desenvolvido neste documento foca-se em estudar/desenvolver metodologias/processos que permitam ajudar os utilizadores a encontrar respostas exactas/corretas para questões complexas que não podem ser respondidas fazendo uso dos sistemas tradicionais. Tal inclui: (i) Ultrapassar a dificuldade dos utilizadores visionarem o esquema subjacente aos repositórios de conhecimento; (ii) Fazer a ponte entre a linguagem natural expressa pelos utilizadores e a linguagem (formal) entendível pelos repositórios; (iii) Processar e retornar informações relevantes que respondem apropriadamente às questões dos utilizadores. Para esse efeito, são identificadas um conjunto de funcionalidades que são consideradas necessárias para suportar o utilizador na resposta a questões complexas. É também fornecida uma descrição formal dessas funcionalidades. A proposta é materializada num protótipo que implementa as funcionalidades previamente descritas. As experiências realizadas com o protótipo desenvolvido demonstram que os utilizadores efectivamente beneficiam das funcionalidades apresentadas: ▪ Pois estas permitem que os utilizadores naveguem eficientemente sobre os repositórios de informação; ▪ O fosso entre as conceptualizações dos diferentes intervenientes é minimizado; ▪ Os utilizadores conseguem responder a questões complexas que não conseguiam responder com os sistemas tradicionais. Em suma, este documento apresenta uma proposta que comprovadamente permite, de forma orientada pelo utilizador, responder a questões complexas em repositórios semiestruturados.

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Magdeburg, Univ., Fak. für Informatik, Diss., 2010

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The need for a convergence between semi-structured data management and Information Retrieval techniques is manifest to the scientific community. In order to fulfil this growing request, W3C has recently proposed XQuery Full Text, an IR-oriented extension of XQuery. However, the issue of query optimization requires the study of important properties like query equivalence and containment; to this aim, a formal representation of document and queries is needed. The goal of this thesis is to establish such formal background. We define a data model for XML documents and propose an algebra able to represent most of XQuery Full-Text expressions. We show how an XQuery Full-Text expression can be translated into an algebraic expression and how an algebraic expression can be optimized.

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OBJECTIVE: Visual hallucinations are under-reported by patients and are often undiscovered by health professionals. There is no gold standard available to assess hallucinations. Our objective was to develop a reliable, valid, semi-structured interview for identifying and assessing visual hallucinations in older people with eye disease and cognitive impairment. METHODS: We piloted the North-East Visual Hallucinations Interview (NEVHI) in 80 older people with visual and/or cognitive impairment (patient group) and 34 older people without known risks of hallucinations (control group). The informants of 11 patients were interviewed separately. We established face validity, content validity, criterion validity, inter-rater agreement and the internal consistency of the NEVHI, and assessed the factor structure for questions evaluating emotions, cognitions, and behaviours associated with hallucinations. RESULTS: Recurrent visual hallucinations were common in the patient group (68.8%) and absent in controls (0%). The criterion, face and content validities were good and the internal consistency of screening questions for hallucinations was high (Cronbach alpha: 0.71). The inter-rater agreements for simple and complex hallucinations were good (Kappa 0.72 and 0.83, respectively). Four factors associated with experiencing hallucinations (perceived control, pleasantness, distress and awareness) were identified and explained a total variance of 73%. Informants gave more 'don't know answers' than patients throughout the interview (p = 0.008), especially to questions evaluating cognitions and emotions associated with hallucinations (p = 0.02). CONCLUSIONS: NEVHI is a comprehensive assessment tool, helpful to identify the presence of visual hallucinations and to quantify cognitions, emotions and behaviours associated with hallucinations.

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Several works deal with 3D data in SLAM problem. Data come from a 3D laser sweeping unit or a stereo camera, both providing a huge amount of data. In this paper, we detail an efficient method to extract planar patches from 3D raw data. Then, we use these patches in an ICP-like method in order to address the SLAM problem. Using ICP with planes is not a trivial task. It needs some adaptation from the original ICP. Some promising results are shown for outdoor environment.

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We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.

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The presentation describes the researcher’s experience of undertaking sensitive interviews. Background The interviews form part of a current study that is examining bereaved parents’ experience of caring for their child at home as well as the experience of their GP. This study builds on earlier work that found general practitioners (GPs) were at times uncertain of their role in paediatric palliative care and questioned whether their involvement had been beneficial to the child and family. The rarity of childhood cancer deaths makes it difficult for GPs to develop or maintain palliative care knowledge and skills yet the GP is perceived as the gatekeeper for care within the community. Presentation aim To describe the process of both the preparation for, and undertaking of, sensitive interviews. Study methodology The methodology incorporates tape-recorded semi-structured interviews, thematic framework analysis and Q methodology (QM). QM will be used to capture the experiences of GPs who have cared for a child with cancer receiving palliative care as well the perspectives of care experienced by the families. The semi-structured interview sample comprises 10 families (parents/guardians) whose child has been treated at a regional childhood cancer centre and their GPs. A further 40-60 GPs will be involved in the QM. Findings The preparation for these interviews will be discussed and compared to the supportive bereavement visits undertaken within the researcher’s role as a paediatric Macmillan nurse. The experience of undertaking the interviews will be exemplified with findings from the initial and the current, study. Papers’ contribution The researcher’s experience of preparing for and undertaking sensitive interviews may prove beneficial to other researchers.

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Discovery Driven Analysis (DDA) is a common feature of OLAP technology to analyze structured data. In essence, DDA helps analysts to discover anomalous data by highlighting 'unexpected' values in the OLAP cube. By giving indications to the analyst on what dimensions to explore, DDA speeds up the process of discovering anomalies and their causes. However, Discovery Driven Analysis (and OLAP in general) is only applicable on structured data, such as records in databases. We propose a system to extend DDA technology to semi-structured text documents, that is, text documents with a few structured data. Our system pipeline consists of two stages: first, the text part of each document is structured around user specified dimensions, using semi-PLSA algorithm; then, we adapt DDA to these fully structured documents, thus enabling DDA on text documents. We present some applications of this system in OLAP analysis and show how scalability issues are solved. Results show that our system can handle reasonable datasets of documents, in real time, without any need for pre-computation.

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Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física