Academic literature on the topic 'Multiple sources of evidences'

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Journal articles on the topic "Multiple sources of evidences"

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Yang, Jian-Ping, Hong-Zhong Huang, Yu Liu, and Yan-Feng Li. "Quantification Classification Algorithm of Multiple Sources of Evidence." International Journal of Information Technology & Decision Making 14, no. 05 (2015): 1017–34. http://dx.doi.org/10.1142/s0219622014500242.

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Although Dempster–Shafer (D–S) evidence theory and its reasoning mechanism can deal with imprecise and uncertain information by combining cumulative evidences for changing prior opinions of new evidences, there is a deficiency in applying classical D–S evidence theory combination rule when conflict evidence appear — conflict evidence causes counter-intuitive results. To address this issue, alternative combination rules have been proposed for resolving the appeared conflicts of evidence. An underlying assumption is that conflict evidences exist, which, however, is not always true. Moreover, it has been verified that conflict factors may not be accurate to characterize the degree of conflict. Instead, the Jousselme distance has been regarded as a quantification criterion for the degree of conflict because of its promising properties. To avoid the counter-intuitive results, multiple sources of evidence should be classified first. This paper proposes a novel algorithm to quantify the classification of multiple sources of evidence based on a core vector method, and the algorithm is further verified by two examples. This study also explores the relationship between complementary information and conflicting evidence and discusses the stochastic interpretation of basic probability assignment functions.
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Levasseur, Sylvain, Jean-Louis Birck, and Claude J. Allègre. "Osmium isotopic composition of corals: evidences for multiple sources." Geochimica et Cosmochimica Acta 63, no. 9 (1999): 1335–43. http://dx.doi.org/10.1016/s0016-7037(99)00017-4.

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Normand, Sharon-Lise T. "Multiple Outcomes and Multiple Sources of Evidence." Circulation: Cardiovascular Quality and Outcomes 4, no. 6 (2011): 579–80. http://dx.doi.org/10.1161/circoutcomes.111.963751.

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Khanuja, Harmeet Kaur, and Dr D. S. Adane. "Forensic Analysis of Databases by Combining Multiple Evidences." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 7, no. 3 (2013): 654–63. http://dx.doi.org/10.24297/ijct.v7i3.3446.

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The information security for securing enterprise databases from internal and external attacks and violations of mutual policy is an interminable struggle. With the growing number of attacks and frauds, the organizations are finding it difficult to meet various regulatory compliance requirements such as SOX, HIPAA, and state privacy laws. The aim here is to develop a methodology which monitors the database transactions on continuous basis and to make a decision whether the database transactions are legitimate or suspicious by combining multiple evidences gathered. The suspicious transactions can then be used for forensic analysis to reconstruct the illegal activity carried out in an organization. This can be achieved by incorporating information accountability in Database Management System. Information accountability means, the information usage should be transparent so that it is possible to determine whether a use is appropriate under a given set of rules. We focus on effective information accountability of data stored in high-performance databases through database forensics which collects and analyses database transactions collected through various sources and artifacts like data cache, log files, error logs etc. having volatile or non-volatile characteristics within high performance databases. The information and multiple evidences collected are then analyzed using an Extended Dempster-Shafer theory(EDST). It  combines multiple such evidences and an initial belief is computed for suspected transactions which can be further used for reconstructing the activity in database forensics process.
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Vlad, Daciana. "Mărturii asupra vârcolacului în cultura tradițioanlă." Anuarul Muzeului Etnograif al Transilvaniei 31 (December 20, 2017): 156–62. http://dx.doi.org/10.47802/amet.2017.31.06.

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The werewolf is, in the Romanian mitology, an extraordinary being, a demon who swallows the Sun and the Moon, thus causing eclipses. Multiple representations of this creature, such as regular animals (wolves and dogs) or even fantastic beings (dragons) have led to a mistery concerning the demon's appearance. The werewolf is the embodiment of evil, which disturbs the order of the world, and any deviation from a community can lead to one becoming a werewolf. So, werewolves, like ghouls, can appear from different sources: unnamed children, malformed children, kin-slayers, even an action that is contrary to a tradition can create a werewolf. A man will become a werewolf during an eclipse and most of the time, it's his soul that will ascend to the sky and devour the Sun and the Moon. If the bond between the soul and the body is broken during this transformation, the soul is lost forever.
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Sun, Jia Ze, Guo Hua Geng, and Xiao Ying Pan. "D-S Algorithm Based on SCO for Matching Fragments." Applied Mechanics and Materials 411-414 (September 2013): 1876–79. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1876.

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The Dempster-Shafer (D-S) evidence theory is an effective method for uncertain information fusion. Because multiple evidences from different sources of different importance or reliability in the reassembling fractured 3D objects are not equally important when they are combined. This paper presents a social cognitive optimization algorithm (SCO) to generate optimal evidence weight values based on historical training data. In the algorithm, a constrained nonlinear optimized model is established, which is solved by SCO. Compared with the two methods, optimization weight D-S proves more effective than the traditional D-S.
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Allen, J. E. "Computational Gene Prediction Using Multiple Sources of Evidence." Genome Research 14, no. 1 (2003): 142–48. http://dx.doi.org/10.1101/gr.1562804.

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Argintaru, D., C. Besliu, A. Jipa, M. Calin, and T. Esanu. "Some evidences of multiple particle sources from nuclear matter jets in He+AT collisions at relativistic energies." Indian Journal of Physics 85, no. 7 (2011): 1169–73. http://dx.doi.org/10.1007/s12648-011-0117-4.

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Lameira, Valdir, Fabiana Alcântara, Dino Chiappori, and Roberto Pereira. "RENEWABLE ENERGIES AND ECONOMIC DEVELOPMENT: EVIDENCES OF STUDY IN PANEL." Brazilian Journal of Operations & Production Management 13, no. 2 (2016): 208. http://dx.doi.org/10.14488/bjopm.2016.v13.n2.a7.

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The concerns with sustainability in environmental and social realm led to an expressive increase in generation of energy of renewable sources in last years. This paper addresses an investigation on possible associations between the increase of renewable energies generation and the economic and financial performance indicators of countries. The multiple linear regressions method is applied to a data panel of the period from 2005 to 2008, in 54 countries. The outcomes point to an association between higher generation of renewable energies and lower GDP growths, higher per capita income and higher investments in gross fixed capital formation, besides other interesting associations.
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RUSSELL, S. S., J. W. ARDEN, and C. T. PILLINGER. "Evidence for Multiple Sources of Diamond from Primitive Chondrites." Science 254, no. 5035 (1991): 1188–91. http://dx.doi.org/10.1126/science.254.5035.1188.

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Dissertations / Theses on the topic "Multiple sources of evidences"

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Zhang, Baoping. "Intelligent Fusion of Evidence from Multiple Sources for Text Classification." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/28198.

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Automatic text classification using current approaches is known to perform poorly when documents are noisy or when limited amounts of textual content is available. Yet, many users need access to such documents, which are found in large numbers in digital libraries and in the WWW. If documents are not classified, they are difficult to find when browsing. Further, searching precision suffers when categories cannot be checked, since many documents may be retrieved that would fail to meet category constraints. In this work, we study how different types of evidence from multiple sources can be intelligently fused to improve classification of text documents into predefined categories. We present a classification framework based on an inductive learning method -- Genetic Programming (GP) -- to fuse evidence from multiple sources. We show that good classification is possible with documents which are noisy or which have small amounts of text (e.g., short metadata records) -- if multiple sources of evidence are fused in an intelligent way. The framework is validated through experiments performed on documents in two testbeds. One is the ACM Digital Library (using a subset available in connection with CITIDEL, part of NSF's National Science Digital Library). The other is Web data, in particular that portion associated with the Cadê Web directory. Our studies have shown that improvement can be achieved relative to other machine learning approaches if genetic programming methods are combined with classifiers such as kNN. Extensive analysis was performed to study the results generated through the GP-based fusion approach and to understand key factors that promote good classification.<br>Ph. D.
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Abell, Meghann Lynn. "Assessing Fraud Risk, Trustworthiness, Reliability, and Truthfulness: Integrating Audit Evidence from Multiple Sources." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/27763.

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To assess fraud risk, auditors collect evidence in a sequential manner by reviewing workpaper documentation, and by collecting corroborating and clarifying information from financial (management) personnel and nonfinancial (operating) personnel. SAS 99 (AICPA, 2002) noted that audit evidence gathered from financial personnel may be susceptible to deception. In addition, prior researchers have found auditors to be poor at detecting deception immediately following deceptive communication. Though the audit process is sequential and iterative, these studies measured auditors– ability to detect deception at a single point and did not provide corroborating evidence after the deceptive communication for auditors to revise their judgments. In this study, I examined auditors’ fraud risk assessments and truthfulness judgments throughout the audit process when there was an attempt at deception by management (financial) personnel. The belief adjustment model provided a framework to examine auditors’ initial judgments, their judgments directly following a deception attempt by financial personnel, and their judgments after receiving corroborating evidence from nonfinancial personnel. Sixty-four experienced auditors electronically completed one of four randomly assigned cases and, within each case, assessed the fraud risk, truthfulness, trustworthiness, and reliability of financial personnel at multiple points for a fictitious client. I manipulated the presence (absence) of fraud and the level of experience of the source of corroborating evidence (operating personnel). I hypothesized that auditors would not be able to differentially evaluate fraud risk and truthfulness judgments of financial personnel between the fraud and no fraud conditions when exposed to workpaper documentation and deceptive client inquiry evidence by management (financial personnel). However, I expected to find that auditors– would update their fraud risk and truthfulness judgments as they reviewed audit evidence from nonfinancial (operating) personnel. The results indicate that auditors in this study are not able to appropriately assess fraud risk and the truthfulness of financial personnel following the review of workpaper and client inquiry evidence. While the client was deceptive in the fraud condition only, auditors did not differentially assess the fraud risk and truthfulness of financial personnel between the fraud and no fraud conditions. After auditors reviewed evidence from nonfinancial personnel, in the presence of fraud, auditors increased their fraud risk and decreased their truthfulness judgments of financial personnel as inconsistent evidence was presented from a corroborating source. Therefore, in the presence of fraud, auditors improved the effectiveness of the audit process by appropriately increasing their fraud risk assessments in light of inconsistent audit evidence from nonfinancial (operating) personnel. Of equal importance, in the absence of fraud, auditors decreased their fraud risk assessments as consistent evidence was presented from a corroborating source. Therefore, auditors increased the efficiency of the audit process by appropriately decreasing their fraud risk assessments after integrating consistent audit evidence from nonfinancial personnel into their judgments. Further, I observed that these auditors revised their fraud risk assessments to a greater extent when audit evidence was provided by a source with a higher level of experience. Though prior research has found auditors to be poor at detecting deception, the results of this study indicate that auditors will increase or decrease their fraud risk assessments and truthfulness judgments based on the consistency of audit evidence gathered from a corroborating source. Therefore, in practice, auditors may be able to detect deception as the audit progresses.<br>Ph. D.
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Faverjon, Céline. "Risk based surveillance for vector-borne diseases in horses : combining multiple sources of evidence to improve decision making." Thesis, Clermont-Ferrand 2, 2015. http://www.theses.fr/2015CLF22604/document.

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Les maladies émergentes à transmission vectorielle sont une préoccupation croissante et particulièrement lorsqu’elles affectent les chevaux, une population spécifiquement à risque vis-à-vis de la propagation de maladies. En effet, les chevaux voyagent fréquemment et, malgré l’impact sanitaire et économique des maladies équines, les règlementations sanitaires et les principes de biosécurité et de traçabilité censés assurer la sécurité des mouvements d'équidés ne sont pas toujours en place. Notre travail propose d'améliorer la surveillance des maladies à transmission vectorielle chez les chevaux en utilisant différentes méthodes pour estimer la probabilité d'émergence d'une maladie. Tout d'abord, nous avons développé un modèle quantitatif et spatio-temporel combinant différentes probabilités pour estimer les risques d'introduction de la peste équine et de l’encéphalose équine. Ces combinaisons permettent d’obtenir une image plus détaillée du risque posé par ces agents pathogènes. Nous avons ensuite évalué des systèmes de surveillance syndromique par deux approches méthodologiques: l'approche classique avec un seuil d'alarme basé sur un multiple de l'erreur standard de prédiction, et l'approche bayésienne basée sur le rapport de vraisemblance. Nous avons travaillé ici principalement sur la détection précoce du virus West Nile en utilisant les symptômes nerveux des chevaux. Les deux approches ont fourni des résultats prometteurs, mais l’approche bayésienne était particulièrement intéressante pour obtenir un résultat quantitatif et pour combiner différentes informations épidémiologiques. Pour finir, l'approche bayésienne a été utilisée pour combiner quantitativement différentes sources d'estimation du risque : surveillance syndromique multivariée, et combinaison de la surveillance syndromique avec les résultats d’analyses de risques. Ces combinaisons ont données des résultats prometteurs. Ce travail, basé sur des estimations de risque, contribue à améliorer la surveillance des maladies à transmission vectorielle chez les chevaux et facilite la prise de décision. Les principales perspectives de ce travail sont d'améliorer la collecte et le partage de données, de mettre en oeuvre une évaluation complète des performances des systèmes de surveillance multivariés, et de favoriser l'adoption de ce genre d’approche par les décideurs en utilisant une interface conviviale et en mettant en place un transfert de connaissance<br>Emerging vector-borne diseases are a growing concern, especially for horse populations, which are at particular risk for disease spread. In general, horses travel widely and frequently and, despite the health and economic impacts of equine diseases, effective health regulations and biosecurity systems to ensure safe equine movements are not always in place. The present work proposes to improve the surveillance of vector-borne diseases in horses through the use of different approaches that assess the probability of occurrence of a newly introduced epidemic. First, we developed a spatiotemporal quantitative model which combined various probabilities in order to estimate the risk of introduction of African horse sickness and equine encephalosis. Such combinations of risk provided more a detailed picture of the true risk posed by these pathogens. Second, we assessed syndromic surveillance systems using two approaches: a classical approach with the alarm threshold based on the standard error of prediction, and a Bayesian approach based on a likelihood ratio. We focused particularly on the early detection of West Nile virus using reports of nervous symptoms in horses. Both approaches provided interesting results but Bayes’ rule was especially useful as it provided a quantitative output and was able to combine different epidemiological information. Finally, a Bayesian approach was also used to quantitatively combine various sources of risk estimation in a multivariate syndromic surveillance system, as well as a combination of quantitative risk assessment with syndromic surveillance (applied to West Nile virus and equine encephalosis, respectively). Combining evidence provided promising results. This work, based on risk estimations, strengthens the surveillance of VBDs in horses and can support public health decision making. It also, however, highlights the need to improve data collection and data sharing, to implement full performance assessments of complex surveillance systems, and to use effective communication and training to promote the adoption of these approaches
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Lima, Márcia Sampaio. "Identificando o Tópico de Páginas Web." Universidade Federal do Amazonas, 2009. http://tede.ufam.edu.br/handle/tede/2957.

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Made available in DSpace on 2015-04-11T14:03:16Z (GMT). No. of bitstreams: 1 DISSERTACAO MARCIA.pdf: 794477 bytes, checksum: 2cef05b5eceb08ee3829eec46ac4a278 (MD5) Previous issue date: 2009-04-24<br>Fundação de Amparo à Pesquisa do Estado do Amazonas<br>Textual and structural sources of evidences extracted from web pages are frequently used to improve the results of Information Retrieval (IR) systems. The main topic of a web page is a textual source of evidence that has a wide applicability in IR systems. It can be used as a new source of evidence to improve ranking results, page classification, filtering, among other applications. In this work, we propose to study, develop and evaluate a method to identify the main topic of a web page using a combination of different sources of evidences. We define the main topic of a web page as a set of, at most, five distinct keywords related to the main subject of the page. In general, the proposed method, is divided in four distinct phases: (1) identification of the keywords that describe the web page content, using multiple sources of evidences; (2) use of a genetic algorithm to combine the sources of evidences; (3) definition of the three better keywords of the page; and (4) use of a web directory to identify the page main topic. The results of the experiments show that: (1) the best source of evidence used to describe the keywords of a web page is the content link; (2) the proposed method is efficient to identify the main topic of a web page: 0.9129, in a scale of zero to one; and (3) the proposed method is also efficient to automatic classify web pages within the Google directory, reaching 88%±0.11 of precision in the classification task.<br>Evidências textuais e estruturais que podem ser extraídas dos documentos web são frequentemente usadas na busca pela melhoria da qualidade dos resultados obtidos pelos diversos sistemas de recuperação de informação (RI). O tópico de uma página web é uma evidência textual que possui uma vasta aplicabilidade nesses sistemas, podendo servir como uma nova fonte de evidência para melhorar ranking de páginas web, melhorar sistemas de classificação e filtragem destas páginas, entre outros. O presente trabalho tem por objetivo estudar, desenvolver e avaliar um método para identificar automaticamente o tópico de páginas web através da combinação de diferentes fontes de evidências. Definimos o tópico de uma página como sendo um conjunto de, no máximo, cinco termos distintos relacionadas ao assunto principal da página. Em linhas gerais, o método de identificação de tópicos proposto nesta dissertação, está dividido em quatro fases distintas: (1) identificação dos possíveis termos descritores de uma página web, fazendo uso de múltiplas fontes de evidências; (2) utilização de um algoritmo genético na combinação das fontes de evidências usadas; (3) definição dos três melhores termos descritores da página; e (4) utilização da estrutura hierárquica de um diretório abrangente e popular da web com o objetivo de identificar o tópico da referida página. Os resultados obtidos nos experimentos realizados para avaliar o método proposto foram os seguintes: (1) alto grau de importância do uso da concatenação do texto de âncora de links na descoberta dos termos descritores de uma página web; (2) boa avaliação da eficiência do método proposto na identificação de tópicos de páginas web: 0.9129, em uma escala de zero a um; e (3) boa avaliação da utilização de parte do método proposto na classificação automática de páginas web na estrutura hierárquica do diretório Google, atingindo 88%±0.11 de acertos das páginas classificadas. Os experimentos realizados demonstram que o modelo proposto é útil na identificação do tópico de uma página web e também na classificação de páginas na estrutura hierárquica do diretório Google.
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Zhang, Ping. "Learning from Multiple Knowledge Sources." Diss., Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214795.

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Computer and Information Science<br>Ph.D.<br>In supervised learning, it is usually assumed that true labels are readily available from a single annotator or source. However, recent advances in corroborative technology have given rise to situations where the true label of the target is unknown. In such problems, multiple sources or annotators are often available that provide noisy labels of the targets. In these multi-annotator problems, building a classifier in the traditional single-annotator manner, without regard for the annotator properties may not be effective in general. In recent years, how to make the best use of the labeling information provided by multiple annotators to approximate the hidden true concept has drawn the attention of researchers in machine learning and data mining. In our previous work, a probabilistic method (i.e., MAP-ML algorithm) of iteratively evaluating the different annotators and giving an estimate of the hidden true labels is developed. However, the method assumes the error rate of each annotator is consistent across all the input data. This is an impractical assumption in many cases since annotator knowledge can fluctuate considerably depending on the groups of input instances. In this dissertation, one of our proposed methods, GMM-MAPML algorithm, follows MAP-ML but relaxes the data-independent assumption, i.e., we assume an annotator may not be consistently accurate across the entire feature space. GMM-MAPML uses a Gaussian mixture model (GMM) and Bayesian information criterion (BIC) to find the fittest model to approximate the distribution of the instances. Then the maximum a posterior (MAP) estimation of the hidden true labels and the maximum-likelihood (ML) estimation of quality of multiple annotators at each Gaussian component are provided alternately. Recent studies show that it is not the case that employing more annotators regardless of their expertise will result in improved highest aggregating performance. In this dissertation, we also propose a novel algorithm to integrate multiple annotators by Aggregating Experts and Filtering Novices, which we call AEFN. AEFN iteratively evaluates annotators, filters the low-quality annotators, and re-estimates the labels based only on information obtained from the good annotators. The noisy annotations we integrate are from any combination of human and previously existing machine-based classifiers, and thus AEFN can be applied to many real-world problems. Emotional speech classification, CASP9 protein disorder prediction, and biomedical text annotation experiments show a significant performance improvement of the proposed methods (i.e., GMM-MAPML and AEFN) as compared to the majority voting baseline and the previous data-independent MAP-ML method. Recent experiments include predicting novel drug indications (i.e., drug repositioning) for both approved drugs and new molecules by integrating multiple chemical, biological or phenotypic data sources.<br>Temple University--Theses
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Stevenson, Robert Mark. "Multiple knowledge sources for word sense disambiguation." Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310763.

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Dench, M. "Structural vibration control using multiple synchronous sources." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/349006/.

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The advantages of isolating vibrating machinery from its supporting structure are that the chances of vibration induced fatigue failure of structural components are reduced, the structure becomes more inhabitable for people due to less vibration exposure and the sound radiated by the structure into the environment is reduced. This last point is especially important for machinery operating in a marine environment because low frequency sound propagates very well underwater, and the machinery induced sound radiated from a ship or submarine is a primary detection and classification mechanism for passive sonar systems. This thesis investigates the control of vibration from an elastic support structure upon which multiple vibrating systems are passively mounted. The excitations are assumed to occur at discrete frequencies with a finite number of harmonic components and the machines are all assumed to be supplied with power from the same electrical supply. Active vibration control may be achieved by adjusting the phase of the voltage supplied to one or more of the machines, so that a minimum value of a measurable cost function is obtained. Adjusting the phase of a machine with respect to a reference machine is known as synchrophasing and is a well established technique for controlling the sound in aircraft cabins and in ducts containing axial fans. However, the use of the technique for reducing the vibration of machinery mounted on elastic structures seems to have received very little attention in the literature and would appear to be a gap in the current knowledge. This thesis aims to address that gap by investigating theoretically and experimentally how synchrophasing can be implemented as an active structural vibration control technique.
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MEDEIROS, Ícaro Rafael da Silva. "Tag suggestion using multiple sources of knowledge." Universidade Federal de Pernambuco, 2010. https://repositorio.ufpe.br/handle/123456789/2275.

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Made available in DSpace on 2014-06-12T15:56:06Z (GMT). No. of bitstreams: 2 arquivo2739_1.pdf: 2586871 bytes, checksum: 3a0e10a22b131714039f0e8ffe875d80 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010<br>Nos sistemas de tagging social usuários atribuem tags (palavras-chave) a recursos (páginas Web, fotos, publicações, etc), criando uma estrutura conhecida como folksonomia, que possibilita uma melhora na navegação, organização e recuperação de informação. Atualmente, esses sistemas são muito populares na Web, portanto, melhorar sua qualidade e automatizar o processo de atribuição de tags é uma tarefa importante. Neste trabalho é proposto um sistema que automaticamente atribui tags a páginas, baseando-se em múltiplas fontes de conhecimento como o conteúdo textual, estrutura de hiperlinks e bases de conhecimento. A partir dessas fontes, vários atributos são extraídos para construir um classificador que decide que termos devem ser sugeridos como tag. Experimentos usando um dataset com tags e páginas extraídas do Delicious, um importante sistema de tagging social, mostram que nossos métodos obtém bons resultados de precisão e cobertura, quando comparado com tags sugeridas por usuários. Além disso, uma comparação com trabalhos relacionados mostra que nosso sistema tem uma qualidade de sugestão comparável a abordagens estado da arte na área. Finalmente, uma avaliação com usuários foi feita para simular um ambiente real, o que também produziu bons resultados
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Rice, Michael, and Erik Perrins. "Maximum Likelihood Detection from Multiple Bit Sources." International Foundation for Telemetering, 2015. http://hdl.handle.net/10150/596443.

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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<br>This paper deals with the problem of producing the best bit stream from a number of input bit streams with varying degrees of reliability. The best source selector and smart source selector are recast as detectors, and the maximum likelihood bit detector (MLBD) is derived from basic principles under the assumption that each bit value is accompanied by a quality measure proportional to its probability of error. We show that both the majority voter and the best source selector are special cases of the MLBD and define the conditions under which these special cases occur. We give a mathematical proof that the MLBD is the same as or better than the best source selector.
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Kabzinska, Ewa Joanna. "Empirical likelihood approach for estimation from multiple sources." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/422166/.

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Empirical likelihood is a non-parametric, likelihood-based inference approach. In the design-based empirical likelihood approach introduced by Berger and De La Riva Torres (2016), the parameter of interest is expressed as a solution to an estimating equation. The maximum empirical likelihood point estimator is obtained by maximising the empirical likelihood function under a system of constraints. A single vector of weights, which can be used to estimate various parameters, is created. Design-based empirical likelihood confidence intervals are based on the χ<sup>2</sup> approximation of the empirical likelihood ratio function. The confidence intervals are range-preserving and asymmetric, with the shape driven by the distribution of the data. In this thesis we focus on the extension and application of design-based empirical likelihood methods to various problems occurring in survey inference. First, a design-based empirical likelihood methodology for parameter estimation in two surveys context, in presence of alignment and benchmark constraints, is developed. Second, a design-based empirical likelihood multiplicity adjusted estimator for multiple frame surveys is proposed. Third, design-based empirical likelihood is applied to a practical problem of census coverage estimation. The main contribution of this thesis is defining the empirical likelihood methodology for the studied problems and showing that the aligned and multiplicity adjusted empirical likelihood estimators are √n-design-consistent. We also discuss how the original proofs presented by Berger and De La Riva Torres (2016) can be adjusted to show that the empirical likelihood ratio statistic is pivotal and follows a χ<sup>2</sup> distribution under alignment constraints and when the multiplicity adjustments are used. We evaluate the asymptotic performance of the empirical likelihood estimators in a series of simulations on real and artificial data. We also discuss the computational aspects of the calculations necessary to obtain empirical likelihood point estimates and confidence intervals and propose a practical way to obtain empirical likelihood confidence intervals in situations when they might be difficult to obtain using standard approaches.
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Books on the topic "Multiple sources of evidences"

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Pant, Raghab D. Sources of inflation in Asia: Theory and evidences. Nirala Publications, 1988.

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Bock, Mary Ellen, and Nancy J. Kirkendall, eds. Improving Crop Estimates by Integrating Multiple Data Sources. National Academies Press, 2017. http://dx.doi.org/10.17226/24892.

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Groves, Robert M., and Brian A. Harris-Kojetin, eds. Federal Statistics, Multiple Data Sources, and Privacy Protection. National Academies Press, 2017. http://dx.doi.org/10.17226/24893.

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Viney, Donald Wayne. A philosopher looks at the Bible. Friends of Timmons Chapel, Pittsburg State University, 1992.

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Njozi, Hamza M. The sources of the Qur'an: A critical review of the authorship theories. World Assembly of Muslim Youth, 2000.

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Colinet, Jay. Dust sources and controls for multiple-machine longwall faces. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Colinet, Jay. Dust sources and controls for multiple-machine longwall faces. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Kidokkyo sŏngsŏ ŭi ihae. Tʻongnamu, 2007.

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Bock, Darrell L. Can I trust the Bible? / Darrell L. Bock; [introduction by Ravi Zacharias]. InterVarsity Press, 2007.

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Doherty, Neil A. Additive and multiplicative risk premium with multiple sources of risk. College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1987.

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Book chapters on the topic "Multiple sources of evidences"

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Shull, Forrest, and Raimund L. Feldmann. "Building Theories from Multiple Evidence Sources." In Guide to Advanced Empirical Software Engineering. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-044-5_13.

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Savoy, Jacques. "Report on CLEF 2002 Experiments: Combining Multiple Sources of Evidence." In Advances in Cross-Language Information Retrieval. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45237-9_6.

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Miller, Robert. "Evidence for Multiple Sources of Theta Generation in the Hippocampus and Related Structures." In Cortico-Hippocampal Interplay and the Representation of Contexts in the Brain. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-662-21732-0_7.

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Cook, Simon J., Susan Palmer, Robin Plevin, and Michael J. O. Wakelam. "Multiple sources of sn-1,2-diacylglycerol in mitogen-stimulated Swiss 3T3 cells; evidence for activation of phosphoinositidase C and PtdChophospholipase D." In Biological Signal Transduction. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-75136-3_30.

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Schwartz, Jennifer, and Darrell Steffensmeier. "Stability and Change in Girls’ Delinquency and the Gender Gap: Trends in Violence and Alcohol Offending Across Multiple Sources of Evidence." In Delinquent Girls. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0415-6_1.

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Dubois, Didier, and Henri Prade. "A Set-Valued Approach to Multiple Source Evidence." In Advances in Artificial Intelligence: From Theory to Practice. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60045-1_14.

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Jiang, Jiaojiao, Sheng Wen, Shui Yu, Bo Liu, Yang Xiang, and Wanlei Zhou. "Identifying Multiple Propagation Sources." In Malicious Attack Propagation and Source Identification. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02179-5_11.

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Fleischmann, Moritz. "Impact of Multiple Sources." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56691-2_9.

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Pivert, Olivier, and Henri Prade. "Querying Uncertain Multiple Sources." In Lecture Notes in Computer Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11508-5_24.

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Joseph, Brian D. "Multiple sources and multiple causes multiply explored." In Benjamins Current Topics. John Benjamins Publishing Company, 2015. http://dx.doi.org/10.1075/bct.79.08jos.

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Conference papers on the topic "Multiple sources of evidences"

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Sigurbjörnsson, Börkur, Jaap Kamps, and Maarten de Rijke. "Multiple sources of evidence for XML retrieval." In the 27th annual international conference. ACM Press, 2004. http://dx.doi.org/10.1145/1008992.1009117.

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Jung, Yuchul, Yoonjung Choi, and Sung-Hyon Myaeng. "Determining Mood for a Blog by Combining Multiple Sources of Evidence." In IEEE/WIC/ACM International Conference on Web Intelligence (WI'07). IEEE, 2007. http://dx.doi.org/10.1109/wi.2007.140.

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Frery, A., A. Correia, and C. Freitas. "Multifrequency Full Polarimetric SAR Classification with Multiple Sources of Statistical Evidence." In 2006 IEEE International Symposium on Geoscience and Remote Sensing. IEEE, 2006. http://dx.doi.org/10.1109/igarss.2006.1076.

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Yew, Chern Har, and Hanan Lutfiyya. "A middleware and algorithms for trust calculation from multiple evidence sources." In 2012 7th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). IEEE, 2012. http://dx.doi.org/10.1109/seams.2012.6224394.

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Di Buccio, Emanuele, and Massimo Melucci. "Toward the design of a methodology to predict relevance through multiple sources of evidence." In the 3rd workshop. ACM Press, 2010. http://dx.doi.org/10.1145/1871902.1871918.

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Harrison, Lauren N., Dominique Weis, and Michael O. Garcia. "THE HAWAIIAN MANTLE PLUME OVER >81 MILLION YEARS: EVIDENCE FOR MULTIPLE DEPLETED SOURCES." In GSA Annual Meeting in Seattle, Washington, USA - 2017. Geological Society of America, 2017. http://dx.doi.org/10.1130/abs/2017am-307265.

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Huang, Chenchen, Yanhong Zeng, Xiaojun Luo, and Bixian Mai. "Tracing the Sources and Microbial Degradation of PCBs in Field Sediments by a Multiple-Line-Of-Evidence Approach." In Goldschmidt2020. Geochemical Society, 2020. http://dx.doi.org/10.46427/gold2020.1088.

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Balbiani, Philippe, David Fernández-Duque, Andreas Herzig, and Emiliano Lorini. "Stratified Evidence Logics." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/211.

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Abstract:
Evidence logics model agents' belief revision process as they incorporate and aggregate information obtained from multiple sources. This information is captured using neighbourhood structures, where individual neighbourhoods represent pieces of evidence. In this paper we propose an extended framework which allows one to explicitly quantify either the number of evidence sets, or effort, needed to justify a given proposition, provide a complete deductive calculus and a proof of decidability, and show how existing frameworks can be embedded into ours.
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Cuntoor, N., A. Kale, and R. Chellappa. "Combining multiple evidences for gait recognition." In 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698). IEEE, 2003. http://dx.doi.org/10.1109/icme.2003.1221261.

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Naguib, Ahmed M., and Sukhan Lee. "Adaptive Bayesian recognition with multiple evidences." In 2014 International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2014. http://dx.doi.org/10.1109/icmcs.2014.6911153.

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Reports on the topic "Multiple sources of evidences"

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Ditterich, Jochen. Neural and Computational Mechanisms of Perceptual Decisions Between Multiple Alternatives Based on Multiple Sources of Evidence. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada567245.

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Penning de Vries, F., and S. Ruaysoongnern. Multiple sources of water for multiple purposes in north east Thailand. International Water Management Institute (IWMI), 2010. http://dx.doi.org/10.5337/2010.208.

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Schwartz, Richard, and John Makhoul. Combining Multiple Knowledge Sources for Speech Recognition. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada198928.

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Shelton, Christian R. Balancing Multiple Sources of Reward in Reinforcement Learning. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada454702.

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Coupey, Eloise, Mark T. Jones, and Haiyuan Wang. TEAMDEC: Integrative Decision Solutions with Multiple Information Sources. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada386716.

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Arens, Yigal, Chin Y. Chee, Chun-Nan Hsu, and Craig A. Knoblock. Retrieving and Integrating Data from Multiple Information Sources. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada269588.

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Ahn, J., P. L. Chambre, T. H. Pigford, and W. W. L. Lee. Radionuclide dispersion from multiple patch sources into a rock fracture. Office of Scientific and Technical Information (OSTI), 1986. http://dx.doi.org/10.2172/5539594.

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Engberg, John, Dennis Epple, Jason Imbrogno, Holger Sieg, and Ron Zimmer. Estimation of Causal Effects in Experiments with Multiple Sources of Noncompliance. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w14842.

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Hackel, L. A., and K. McKinney. Multiple Beam Laser Light Sources Final Report CRADA No. TC-739-94. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1406416.

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Mungiole, Michael, and Alan Wetmore. COMBIC Modifications to Determine Aerosol Cloud Densities for Multiple Obscurant Input Sources. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada392771.

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