891 resultados para 080704 Information Retrieval and Web Search
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Includes bibliography
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência da Computação - IBILCE
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Pós-graduação em Ciência da Informação - FFC
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Introduction: In the digital environment, metadata influence both in data access and information retrieval and are used as search elements to facilitate locating resources on the Web. Objective: In this perspective, the aim is to present the methodology BEAM, developed in Biblioteca de Estudos e Aplicação de Metadados, of the Research Group “Novas Tecnologias em Informação” in Universidade Estadual Paulista and used to define the metadata for describing information resources. Methodology: The methodology used for the construction of the research is exploratory and bibliographic and was developed based on the theoretical method Chuttur (2011) and the life cycle of data from the DataOne (2012) and also the PDCA cycle and tool 5W1H . Results: The seven steps of the methodology are presented and also the necessary guidelines for their implementation. Conclusions: We conclude pointing BEAM methodology that can be adopted by libraries in the construction of catalogs aimed at meeting the needs of users.
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Information retrieval is a recurrent subject in search of information science. This kind of study aim to improve results in both searches on the Web and in various other digital information environment. In this context, the Iterative Representation model suggested for digital repositories, appears as a differential that changes the paradigm of self-archiving of digital objects, creating a concept of relationship between terms that link the user thought the material deposited in the digital environment. The links effect by the Iterative Representation aided Assisted Folksonomy generate a shaped structure that connects networks, vertically and horizontally, the objects deposited, relying on some kind of structure for representing knowledge of specialty areas and therefore, creating an information network based on knowledge of users. The network of information created, called the network of tags is dynamic and effective a different model of information retrieval and study of digital information repositories.Keywords Digital Repositories; Iterative Representation; Folksonomy; Folksonomy Assisted; Semantic Web; Network Tags.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shed light on the relationship between semantic and structural parameters of complex networks. They also indicate that when combined with traditional techniques the complex network approach may be useful to enhance the discrimination of senses in large texts. Copyright (C) EPLA, 2012
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For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.
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The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.
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Introduction Current empirical findings indicate that the efficiency of decision making (both for experts and near-experts) in simple situations is reduced under increased stress (Wilson, 2008). Explaining the phenomenon, the Attentional Control Theory (ACT, Eysenck et al., 2007) postulates an impairment of attentional processes resulting in a less efficient processing of visual information. From a practitioner’s perspective, it would be highly relevant to know whether this phenomenon can also be found in complex sport situations like in the game of football. Consequently, in the present study, decision making of football players was examined under regular vs. increased anxiety conditions. Methods 22 participants (11 experts and 11 near-experts) viewed 24 complex football situations (counterbalanced) in two anxiety conditions from the perspective of the last defender. They had to decide as fast and accurate as possible on the next action of the player in possession (options: shot on goal, dribble or pass to a designated team member) for equal numbers of trials in a near and far distance condition (based on the position of the player in possession). Anxiety was manipulated via a competitive environment, false feedback as well as ego threats. Decision time and accuracy, gaze behaviour (e.g., fixation duration on different locations) as well as state anxiety and mental effort were used as dependent variables and analysed with 2 (expertise) x 2 (distance) x 2 (anxiety) ANOVAs with repeated measures on the last two factors. Besides expertise differences, it was hypothesised that, based on ACT, increased anxiety reduces performance efficiency and impairs gaze behaviour. Results and Discussion Anxiety was manipulated successfully, indicated by higher ratings of state anxiety, F(1, 20) = 13.13, p < .01, ηp2 = .40. Besides expertise differences in decision making – experts responded faster, F(1, 20) = 11.32, p < .01, ηp2 = .36, and more accurate, F(1,20) = 23.93, p < .01, ηp2 = .55, than near-experts – decision time, F(1, 20) = 9.29, p < .01, ηp2 = .32, and mental effort, F(1, 20) = 7.33, p = .01, ηp2 = .27, increased for both groups in the high anxiety condition. This result confirms the ACT assumption that processing efficiency is reduced when being anxious. Replicating earlier findings, a significant expertise by distance interaction could be observed, F(1, 18) = 18.53, p < .01, ηp2 = .51), with experts fixating longer on the player in possession or the ball in the near distance and longer on other opponents, teammates and free space in the far distance condition. This shows that experts are able to adjust their gaze behaviour to affordances of displayed playing patterns. Additionally, a three way interaction was found, F(1, 18) = 7.37 p = .01, ηp2 = .29, revealing that experts utilised a reduced number of fixations in the far distance condition when being anxious indicating a reduced ability to pick up visual information. Since especially the visual search behaviour of experts was impaired, the ACT prediction that particularly top-down processes are affected by anxiety could be confirmed. Taken together, the results show that sports performance is negatively influenced by anxiety since longer response times, higher mental effort and inefficient visual search behaviour were observed. From a practitioner’s perspective, this finding might suggest preferring (implicit) perceptual cognitive training; however, this recommendation needs to be empirically supported in intervention studies. References: Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336-353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. Int. Review of Sport and Exercise Psychology, 1, 184-201.
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This paper describes the first set of experiments defined by the MIRACLE (Multilingual Information RetrievAl for the CLEf campaign) research group for some of the cross language tasks defined by CLEF. These experiments combine different basic techniques, linguistic-oriented and statistic-oriented, to be applied to the indexing and retrieval processes.
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La nanotecnología es un área de investigación de reciente creación que trata con la manipulación y el control de la materia con dimensiones comprendidas entre 1 y 100 nanómetros. A escala nanométrica, los materiales exhiben fenómenos físicos, químicos y biológicos singulares, muy distintos a los que manifiestan a escala convencional. En medicina, los compuestos miniaturizados a nanoescala y los materiales nanoestructurados ofrecen una mayor eficacia con respecto a las formulaciones químicas tradicionales, así como una mejora en la focalización del medicamento hacia la diana terapéutica, revelando así nuevas propiedades diagnósticas y terapéuticas. A su vez, la complejidad de la información a nivel nano es mucho mayor que en los niveles biológicos convencionales (desde el nivel de población hasta el nivel de célula) y, por tanto, cualquier flujo de trabajo en nanomedicina requiere, de forma inherente, estrategias de gestión de información avanzadas. Desafortunadamente, la informática biomédica todavía no ha proporcionado el marco de trabajo que permita lidiar con estos retos de la información a nivel nano, ni ha adaptado sus métodos y herramientas a este nuevo campo de investigación. En este contexto, la nueva área de la nanoinformática pretende detectar y establecer los vínculos existentes entre la medicina, la nanotecnología y la informática, fomentando así la aplicación de métodos computacionales para resolver las cuestiones y problemas que surgen con la información en la amplia intersección entre la biomedicina y la nanotecnología. Las observaciones expuestas previamente determinan el contexto de esta tesis doctoral, la cual se centra en analizar el dominio de la nanomedicina en profundidad, así como en el desarrollo de estrategias y herramientas para establecer correspondencias entre las distintas disciplinas, fuentes de datos, recursos computacionales y técnicas orientadas a la extracción de información y la minería de textos, con el objetivo final de hacer uso de los datos nanomédicos disponibles. El autor analiza, a través de casos reales, alguna de las tareas de investigación en nanomedicina que requieren o que pueden beneficiarse del uso de métodos y herramientas nanoinformáticas, ilustrando de esta forma los inconvenientes y limitaciones actuales de los enfoques de informática biomédica a la hora de tratar con datos pertenecientes al dominio nanomédico. Se discuten tres escenarios diferentes como ejemplos de actividades que los investigadores realizan mientras llevan a cabo su investigación, comparando los contextos biomédico y nanomédico: i) búsqueda en la Web de fuentes de datos y recursos computacionales que den soporte a su investigación; ii) búsqueda en la literatura científica de resultados experimentales y publicaciones relacionadas con su investigación; iii) búsqueda en registros de ensayos clínicos de resultados clínicos relacionados con su investigación. El desarrollo de estas actividades requiere el uso de herramientas y servicios informáticos, como exploradores Web, bases de datos de referencias bibliográficas indexando la literatura biomédica y registros online de ensayos clínicos, respectivamente. Para cada escenario, este documento proporciona un análisis detallado de los posibles obstáculos que pueden dificultar el desarrollo y el resultado de las diferentes tareas de investigación en cada uno de los dos campos citados (biomedicina y nanomedicina), poniendo especial énfasis en los retos existentes en la investigación nanomédica, campo en el que se han detectado las mayores dificultades. El autor ilustra cómo la aplicación de metodologías provenientes de la informática biomédica a estos escenarios resulta efectiva en el dominio biomédico, mientras que dichas metodologías presentan serias limitaciones cuando son aplicadas al contexto nanomédico. Para abordar dichas limitaciones, el autor propone un enfoque nanoinformático, original, diseñado específicamente para tratar con las características especiales que la información presenta a nivel nano. El enfoque consiste en un análisis en profundidad de la literatura científica y de los registros de ensayos clínicos disponibles para extraer información relevante sobre experimentos y resultados en nanomedicina —patrones textuales, vocabulario en común, descriptores de experimentos, parámetros de caracterización, etc.—, seguido del desarrollo de mecanismos para estructurar y analizar dicha información automáticamente. Este análisis concluye con la generación de un modelo de datos de referencia (gold standard) —un conjunto de datos de entrenamiento y de test anotados manualmente—, el cual ha sido aplicado a la clasificación de registros de ensayos clínicos, permitiendo distinguir automáticamente los estudios centrados en nanodrogas y nanodispositivos de aquellos enfocados a testear productos farmacéuticos tradicionales. El presente trabajo pretende proporcionar los métodos necesarios para organizar, depurar, filtrar y validar parte de los datos nanomédicos existentes en la actualidad a una escala adecuada para la toma de decisiones. Análisis similares para otras tareas de investigación en nanomedicina ayudarían a detectar qué recursos nanoinformáticos se requieren para cumplir los objetivos actuales en el área, así como a generar conjunto de datos de referencia, estructurados y densos en información, a partir de literatura y otros fuentes no estructuradas para poder aplicar nuevos algoritmos e inferir nueva información de valor para la investigación en nanomedicina. ABSTRACT Nanotechnology is a research area of recent development that deals with the manipulation and control of matter with dimensions ranging from 1 to 100 nanometers. At the nanoscale, materials exhibit singular physical, chemical and biological phenomena, very different from those manifested at the conventional scale. In medicine, nanosized compounds and nanostructured materials offer improved drug targeting and efficacy with respect to traditional formulations, and reveal novel diagnostic and therapeutic properties. Nevertheless, the complexity of information at the nano level is much higher than the complexity at the conventional biological levels (from populations to the cell). Thus, any nanomedical research workflow inherently demands advanced information management. Unfortunately, Biomedical Informatics (BMI) has not yet provided the necessary framework to deal with such information challenges, nor adapted its methods and tools to the new research field. In this context, the novel area of nanoinformatics aims to build new bridges between medicine, nanotechnology and informatics, allowing the application of computational methods to solve informational issues at the wide intersection between biomedicine and nanotechnology. The above observations determine the context of this doctoral dissertation, which is focused on analyzing the nanomedical domain in-depth, and developing nanoinformatics strategies and tools to map across disciplines, data sources, computational resources, and information extraction and text mining techniques, for leveraging available nanomedical data. The author analyzes, through real-life case studies, some research tasks in nanomedicine that would require or could benefit from the use of nanoinformatics methods and tools, illustrating present drawbacks and limitations of BMI approaches to deal with data belonging to the nanomedical domain. Three different scenarios, comparing both the biomedical and nanomedical contexts, are discussed as examples of activities that researchers would perform while conducting their research: i) searching over the Web for data sources and computational resources supporting their research; ii) searching the literature for experimental results and publications related to their research, and iii) searching clinical trial registries for clinical results related to their research. The development of these activities will depend on the use of informatics tools and services, such as web browsers, databases of citations and abstracts indexing the biomedical literature, and web-based clinical trial registries, respectively. For each scenario, this document provides a detailed analysis of the potential information barriers that could hamper the successful development of the different research tasks in both fields (biomedicine and nanomedicine), emphasizing the existing challenges for nanomedical research —where the major barriers have been found. The author illustrates how the application of BMI methodologies to these scenarios can be proven successful in the biomedical domain, whilst these methodologies present severe limitations when applied to the nanomedical context. To address such limitations, the author proposes an original nanoinformatics approach specifically designed to deal with the special characteristics of information at the nano level. This approach consists of an in-depth analysis of the scientific literature and available clinical trial registries to extract relevant information about experiments and results in nanomedicine —textual patterns, common vocabulary, experiment descriptors, characterization parameters, etc.—, followed by the development of mechanisms to automatically structure and analyze this information. This analysis resulted in the generation of a gold standard —a manually annotated training or reference set—, which was applied to the automatic classification of clinical trial summaries, distinguishing studies focused on nanodrugs and nanodevices from those aimed at testing traditional pharmaceuticals. The present work aims to provide the necessary methods for organizing, curating and validating existing nanomedical data on a scale suitable for decision-making. Similar analysis for different nanomedical research tasks would help to detect which nanoinformatics resources are required to meet current goals in the field, as well as to generate densely populated and machine-interpretable reference datasets from the literature and other unstructured sources for further testing novel algorithms and inferring new valuable information for nanomedicine.
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As a rural state, Ohio has a vital interest in addressing rural health and information needs. NetWellness is a Web-based consumer health information service that focuses on the needs of the residents of Ohio. Health sciences faculty from the state's three Carnegie Research I universities—University of Cincinnati, Case Western Reserve University, and The Ohio State University—create and evaluate content and provide Ask an Expert service to all visitors. Through partnerships at the state and local levels, involving public, private, commercial, and noncommercial organizations, NetWellness has grown from a regional demonstration project in 1995 to a key statewide service. Collaboration with public libraries, complemented by alliances with kindergarten through twelfth grade agencies, makes NetWellness Ohio's essential health information resource.
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Nowadays there is a big amount of biomedical literature which uses complex nouns and acronyms of biological entities thus complicating the task of retrieval specific information. The Genomics Track works for this goal and this paper describes the approach we used to take part of this track of TREC 2007. As this is the first time we participate in this track, we configurated a new system consisting of the following diferenciated parts: preprocessing, passage generation, document retrieval and passage (with the answer) extraction. We want to call special attention to the textual retrieval system used, which was developed by the University of Alicante. Adapting the resources for the propouse, our system has obtained precision results over the mean and median average of the 66 official runs for the Document, Aspect and Passage2 MAP; and in the case of Passage MAP we get nearly the median and mean value. We want to emphasize we have obtained these results without incorporating specific information about the domain of the track. For the future, we would like to further develop our system in this direction.