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Essential notation for object-relational mapping

Torres, Alexandre
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Tese de Doutorado Formato: application/pdf
ENG
Relevância na Pesquisa
46.16%
This thesis presents the Essential Notation for Object-Relational Mapping (ENORM), a general purpose notation that represents structural concepts of Object- Relational Mapping (ORM). The goal of ENORM is to facilitate the design by the clear application of ORM patterns, document mappings with a platform independent notation, and became a repository for model-driven transformations, partial code generation, and round-trip engineering tools. ENORM is a UML profile based notation, designed to represent patterns within a domain modeling logic, with objects of the domain incorporating both behavior and data. The notation represents patterns adopted by widespread ORM frameworks in the market (Active Record, of Ruby; SQLAlchemy, of Python; Entity Framework, of Microsoft .net; JPA, Cayenne, and MyBatis, of Java), following the Don´t Repeat Yourself and Convention over Configuration principles. ENORM was evaluated by controlled experiments, comparing the modeling by students with the use of separated UML and relational models, achieving significantly more goals in the majority of the scenarios, without being significantly different in the worst experimental scenarios.; Esta tese apresenta a Notação Essencial para Mapeamento Objeto-Relacional (em inglês...

Identidade étnica, modelos relacionais e bem-estar na adolescência

Afonso, Filipa Maria de Sousa
Fonte: Instituto Universitário de Lisboa Publicador: Instituto Universitário de Lisboa
Tipo: Dissertação de Mestrado
Publicado em 14/03/2011 POR
Relevância na Pesquisa
46.25%
Mestrado em Psicologia Social e das Organizações; Propomos com este trabalho contribuir para a compreensão da influência da identificação étnica e dos modelos relacionais no bem-estar de adolescentes residentes em Portugal. Os dados foram recolhidos através de questionários de auto-preenchimento por setenta adolescentes com idades compreendidas entre os 15 e os 25 anos em contexto recreativo. No questionário, para avaliar as origens étnicas usou-se a escala Multigroup Ethnic Identity Measures (versão reduzida; MEIM) e medidas comportamentais (música e constituição do grupo de amigos); para analisar os modelos relacionais nos grupos (com família, amigos e professores) foi usada uma escala de Lickel et al (2006); e para avaliar o bem-estar utilizamos a escala de bem-estar psicológico inserida no KIDSCREN-27 (instrumento que avalia a qualidade de vida em crianças e adolescentes) traduzido e adaptado para Portugal (Gaspar & Matos, 2008). Em relação ao bem-estar, os resultados indicam um elevado nível de bem-estar psicológico nos adolescentes, independentemente do seu grupo étnico. Verificaram-se diferenças significativas ao nível das preferências musicais, embora se destaque uma preferência pelo género “ritmos africanos” quer pelos grupos étnicos minoritários...

O impacto da percepção do modelo relacional dominante, por parte dos colaboradores, na satisfação das necessidades psicológicas básicas definidas pela teoria da autodeterminação

Grazina, Nuno Miguel Lourenço
Fonte: Instituto Universitário de Lisboa Publicador: Instituto Universitário de Lisboa
Tipo: Dissertação de Mestrado
Publicado em //2013 POR
Relevância na Pesquisa
46.31%
Dissertação submetida como requisito parcial para obtenção do grau de Mestre em Psicologia Social e das Organizações / The PsycINFO Content Classification Code System: 2900 Social Processes & Social Issues 3000 Social Psychology 3660 Organizational Behavior; A presente investigação procurou perceber de que modo a forma de coodernação numa cultura organizacional influencia a motivação no trabalho. Desta forma, baseamo-nos na Teoria dos Modelos Relacionais (TMR) de Alan Fiske (1991, 1992) e na Teoria da Autodeterminação de Deci & Ryan (1985, 2000) para formar a nossa base teórica de pesquisa. A Teoria dos Modelos Relacionais descreve todas as relações sociais humanas como manifestações de comportamento de quatro construções fundamentais: Communal Sharing, Authority Ranking, Equality Matching e Market Pricing. Por sua vez, a Teoria da Autodeterminação afirma que para o indivíduo ter comportamentos mais autodeterminados e motivações mais intrínsecas devem ser satisfeitas as necessidades de autonomia, competência e relacionamento. Assim, o presente estudo procurou combinar as duas teorias de forma a compreender qual o impacto que a dominância de um Modelo Relacional numa dada organização tem na satisfação das necessidades dos seus colaboradores. Isto é...

Communal sharing and gratitude: how they interrelate

Simão, Cláudia Patrícia Candeias
Fonte: Instituto Universitário de Lisboa Publicador: Instituto Universitário de Lisboa
Tipo: Tese de Doutorado
Publicado em //2013 ENG
Relevância na Pesquisa
46.01%
A Dissertation presented in partial fulfillment of the Requirements for the Degree of Doctor of Psychology / American Psychological Association (PsychINFO Classification Categories and Codes) 3000 Social Psychology 3040 Social Perception and Cognition 2360 Motivation and Emotion; Os indivíduos encontram diariamente amigos, vizinhos, colegas, ou superiores. Estas interações sociais exigem a necessidade de pensar, sentir e comportar-se em cada encontro. A Teoria dos Modelos Relacionais (Fiske, 1992) alega que, para estruturar o mundo social, são utilizadas quatro categorias mentais de relações sociais. A comunhão é uma dessas categorias, representando relações de proximidade formadas através de assimilação consubstancial, como partilhar comida, ou o toque para aumentar a proximidade. A comunhão está relacionada com apoio dentro da relação, existindo, muitas situações propícias a gratidão. Assim, a presente investigação foca-se na relação entre pistas de comunhão, perceção de relações sociais e gratidão. Primeiramente testou-se se os benefícios intencionais levam à implementação de um modelo de comunhão e ao aumento da gratidão. Os resultados revelaram que os benefícios aumentam a gratidão à medida que é implementada comunhão e não igualdade ou hierarquia. Os benefícios ativam diretamente relações de comunhão e indiretamente gratidão. Em segundo...

Gratitude depends on the relational model of communal sharing

Simão, C.; Seibt, B.
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em //2014 ENG
Relevância na Pesquisa
56.33%
WOS:000330283100115 (Nº de Acesso Web of Science); We studied the relation between benefits, perception of social relationships and gratitude. Across three studies, we provide evidence that benefits increase gratitude to the extent to which one applies a mental model of a communal relationship. In Study 1, the communal sharing relational model, and no other relational models, predicted the amount of gratitude participants felt after imagining receiving a benefit from a new acquaintance. In Study 2, participants recalled a large benefit they had received. Applying a communal sharing relational model increased feelings of gratitude for the benefit. In Study 3, we manipulated whether the participant or another person received a benefit from an unknown other. Again, we found that the extent of communal sharing perceived in the relationship with the stranger predicted gratitude. An additional finding of Study 2 was that communal sharing predicted future gratitude regarding the relational partner in a longitudinal design. To conclude, applying a communal sharing model predicts gratitude regarding concrete benefits and regarding the relational partner, presumably because one perceives the communal partner as motivated to meet one's needs. Finally...

Gratitude Depends on the Relational Model of Communal Sharing

Simão, Cláudia; Seibt, Beate
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 22/01/2014 EN
Relevância na Pesquisa
36.27%
We studied the relation between benefits, perception of social relationships and gratitude. Across three studies, we provide evidence that benefits increase gratitude to the extent to which one applies a mental model of a communal relationship. In Study 1, the communal sharing relational model, and no other relational models, predicted the amount of gratitude participants felt after imagining receiving a benefit from a new acquaintance. In Study 2, participants recalled a large benefit they had received. Applying a communal sharing relational model increased feelings of gratitude for the benefit. In Study 3, we manipulated whether the participant or another person received a benefit from an unknown other. Again, we found that the extent of communal sharing perceived in the relationship with the stranger predicted gratitude. An additional finding of Study 2 was that communal sharing predicted future gratitude regarding the relational partner in a longitudinal design. To conclude, applying a communal sharing model predicts gratitude regarding concrete benefits and regarding the relational partner, presumably because one perceives the communal partner as motivated to meet one's needs. Finally, in Study 3, we found in addition that being the recipient of a benefit without opportunity to repay directly increased communal sharing...

Representations and Ensemble Methods for Dynamic Relational Classification

Rossi, Ryan A.; Neville, Jennifer
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 22/11/2011
Relevância na Pesquisa
36.34%
Temporal networks are ubiquitous and evolve over time by the addition, deletion, and changing of links, nodes, and attributes. Although many relational datasets contain temporal information, the majority of existing techniques in relational learning focus on static snapshots and ignore the temporal dynamics. We propose a framework for discovering temporal representations of relational data to increase the accuracy of statistical relational learning algorithms. The temporal relational representations serve as a basis for classification, ensembles, and pattern mining in evolving domains. The framework includes (1) selecting the time-varying relational components (links, attributes, nodes), (2) selecting the temporal granularity, (3) predicting the temporal influence of each time-varying relational component, and (4) choosing the weighted relational classifier. Additionally, we propose temporal ensemble methods that exploit the temporal-dimension of relational data. These ensembles outperform traditional and more sophisticated relational ensembles while avoiding the issue of learning the most optimal representation. Finally, the space of temporal-relational models are evaluated using a sample of classifiers. In all cases, the proposed temporal-relational classifiers outperform competing models that ignore the temporal information. The results demonstrate the capability and necessity of the temporal-relational representations for classification...

RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models

Noessner, Jan; Niepert, Mathias; Stuckenschmidt, Heiner
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.06%
RockIt is a maximum a-posteriori (MAP) query engine for statistical relational models. MAP inference in graphical models is an optimization problem which can be compiled to integer linear programs (ILPs). We describe several advances in translating MAP queries to ILP instances and present the novel meta-algorithm cutting plane aggregation (CPA). CPA exploits local context-specific symmetries and bundles up sets of linear constraints. The resulting counting constraints lead to more compact ILPs and make the symmetry of the ground model more explicit to state-of-the-art ILP solvers. Moreover, RockIt parallelizes most parts of the MAP inference pipeline taking advantage of ubiquitous shared-memory multi-core architectures. We report on extensive experiments with Markov logic network (MLN) benchmarks showing that RockIt outperforms the state-of-the-art systems Alchemy, Markov TheBeast, and Tuffy both in terms of efficiency and quality of results.; Comment: To appear in proceedings of AAAI 2013

Infinite Hidden Relational Models

Xu, Zhao; Tresp, Volker; Yu, Kai; Kriegel, Hans-Peter
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 27/06/2012
Relevância na Pesquisa
46.27%
In many cases it makes sense to model a relationship symmetrically, not implying any particular directionality. Consider the classical example of a recommendation system where the rating of an item by a user should symmetrically be dependent on the attributes of both the user and the item. The attributes of the (known) relationships are also relevant for predicting attributes of entities and for predicting attributes of new relations. In recommendation systems, the exploitation of relational attributes is often referred to as collaborative filtering. Again, in many applications one might prefer to model the collaborative effect in a symmetrical way. In this paper we present a relational model, which is completely symmetrical. The key innovation is that we introduce for each entity (or object) an infinite-dimensional latent variable as part of a Dirichlet process (DP) model. We discuss inference in the model, which is based on a DP Gibbs sampler, i.e., the Chinese restaurant process. We extend the Chinese restaurant process to be applicable to relational modeling. Our approach is evaluated in three applications. One is a recommendation system based on the MovieLens data set. The second application concerns the prediction of the function of yeast genes/proteins on the data set of KDD Cup 2001 using a multi-relational model. The third application involves a relational medical domain. The experimental results show that our model gives significantly improved estimates of attributes describing relationships or entities in complex relational models.; Comment: Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)

The Problem of Time and Quantum Cosmology in the Relational Particle Mechanics Arena

Anderson, Edward
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.29%
This article contains a local solution to the notorious Problem of Time in Quantum Gravity at the conceptual level and which is actually realizable for the relational triangle. The Problem of Time is that `time' in GR and `time' in ordinary quantum theory are mutually incompatible notions, which is problematic in trying to put these two theories together to form a theory of Quantum Gravity. Four frontiers to this resolution in full GR are identified, alongside three further directions not yet conquered even for the relational triangle. This article is also the definitive review on relational particle models originally due to Barbour (2003: dynamics of pure shape) and Barbour and Bertotti (1982: dynamics of shape and scale). These are exhibited as useful toy models of background independence, which I argue to be the `other half' of GR to relativistic gravitation, as well as the originator of the Problem of Time itself. Barbour's work and my localized extension of it are shown to be the classical precursor of the background independence that then manifests itself at the quantum level as the full-blown Problem of Time. In fact 7/8ths of the Isham--Kuchar Problem of Time facets are already present in classical GR; even classical mechanics in relational particle mechanics formulation exhibits 5/8ths of these! In addition to Isham...

Shape Quantities for Relational Quadrilateralland

Anderson, Edward
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.33%
I investigate useful shape quantities for the classical and quantum mechanics of the relational quadrilateral in 2-d. This is relational in the sense that only relative times, relative ratios of separations and relative angles are significant. Relational particle mechanics models such as this paper's have many analogies with the geometrodynamical formulation of general relativity. This renders them suitable as toy models for 1) studying Problem of Time in Quantum Gravity strategies, in particular timeless, semiclassical and histories theory approaches and combinations of these. 2) For consideration of various other quantum-cosmological issues, such as structure formation/inhomogeneity and notions of uniform states and their significance. The relational quadrilateral is more useful in these respects than previously investigated simpler RPM's due to simultaneously possessing linear constraints, nontrivial subsystems and nontrivial complex-projective mathematics. Such shape have been found to be useful in simpler relational models such as the relational triangle and in 1-d.; Comment: Seminar I on relational quadrilaterals (2-d 4-body problem as a whole-universe model in the absense of all absolute connotations). The set of shape quantities given here was found to be incomplete...

Reasoning about Independence in Probabilistic Models of Relational Data

Maier, Marc; Marazopoulou, Katerina; Jensen, David
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.29%
We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to the structure of probabilistic models of relational data inaccurately infers conditional independence. We introduce relational d-separation, a theory for deriving conditional independence facts from relational models. We provide a new representation, the abstract ground graph, that enables a sound, complete, and computationally efficient method for answering d-separation queries about relational models, and we present empirical results that demonstrate effectiveness.; Comment: 61 pages, substantial revisions to formalisms, theory, and related work

On the closure of relational models

Klimova, Anna; Rudas, Tamás
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.06%
Relational models for contingency tables are generalizations of log-linear models, allowing effects associated with arbitrary subsets of cells in a possibly incomplete table, and not necessarily containing the overall effect. In this generality, the MLEs under Poisson and multinomial sampling are not always identical. This paper deals with the theory of maximum likelihood estimation in the case when there are observed zeros in the data. A unique MLE to such data is shown to always exist in the set of pointwise limits of sequences of distributions in the original model. This set is equal to the closure of the original model with respect to the Bregman information divergence. The same variant of iterative scaling may be used to compute the MLE in the original model and in its closure.

Lifted Relational Variational Inference

Choi, Jaesik; Amir, Eyal
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 16/10/2012
Relevância na Pesquisa
36.33%
Hybrid continuous-discrete models naturally represent many real-world applications in robotics, finance, and environmental engineering. Inference with large-scale models is challenging because relational structures deteriorate rapidly during inference with observations. The main contribution of this paper is an efficient relational variational inference algorithm that factors largescale probability models into simpler variational models, composed of mixtures of iid (Bernoulli) random variables. The algorithm takes probability relational models of largescale hybrid systems and converts them to a close-to-optimal variational models. Then, it efficiently calculates marginal probabilities on the variational models by using a latent (or lifted) variable elimination or a lifted stochastic sampling. This inference is unique because it maintains the relational structure upon individual observations and during inference steps.; Comment: Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012)

Discriminative Probabilistic Models for Relational Data

Taskar, Ben; Abbeel, Pieter; Koller, Daphne
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/12/2012
Relevância na Pesquisa
36.32%
In many supervised learning tasks, the entities to be labeled are related to each other in complex ways and their labels are not independent. For example, in hypertext classification, the labels of linked pages are highly correlated. A standard approach is to classify each entity independently, ignoring the correlations between them. Recently, Probabilistic Relational Models, a relational version of Bayesian networks, were used to define a joint probabilistic model for a collection of related entities. In this paper, we present an alternative framework that builds on (conditional) Markov networks and addresses two limitations of the previous approach. First, undirected models do not impose the acyclicity constraint that hinders representation of many important relational dependencies in directed models. Second, undirected models are well suited for discriminative training, where we optimize the conditional likelihood of the labels given the features, which generally improves classification accuracy. We show how to train these models effectively, and how to use approximate probabilistic inference over the learned model for collective classification of multiple related entities. We provide experimental results on a webpage classification task...

Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network

Fan, Xuhui; Da Xu, Richard Yi; Cao, Longbing; Song, Yin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 06/10/2013
Relevância na Pesquisa
46.25%
Effectively modelling hidden structures in a network is very practical but theoretically challenging. Existing relational models only involve very limited information, namely the binary directional link data, embedded in a network to learn hidden networking structures. There is other rich and meaningful information (e.g., various attributes of entities and more granular information than binary elements such as "like" or "dislike") missed, which play a critical role in forming and understanding relations in a network. In this work, we propose an informative relational model (InfRM) framework to adequately involve rich information and its granularity in a network, including metadata information about each entity and various forms of link data. Firstly, an effective metadata information incorporation method is employed on the prior information from relational models MMSB and LFRM. This is to encourage the entities with similar metadata information to have similar hidden structures. Secondly, we propose various solutions to cater for alternative forms of link data. Substantial efforts have been made towards modelling appropriateness and efficiency, for example, using conjugate priors. We evaluate our framework and its inference algorithms in different datasets...

Identifying Independence in Relational Models

Maier, Marc; Jensen, David
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.29%
The rules of d-separation provide a framework for deriving conditional independence facts from model structure. However, this theory only applies to simple directed graphical models. We introduce relational d-separation, a theory for deriving conditional independence in relational models. We provide a sound, complete, and computationally efficient method for relational d-separation, and we present empirical results that demonstrate effectiveness.; Comment: This paper has been revised and expanded. See "Reasoning about Independence in Probabilistic Models of Relational Data" http://arxiv.org/abs/1302.4381

A Sound and Complete Algorithm for Learning Causal Models from Relational Data

Maier, Marc; Marazopoulou, Katerina; Arbour, David; Jensen, David
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 26/09/2013
Relevância na Pesquisa
36.29%
The PC algorithm learns maximally oriented causal Bayesian networks. However, there is no equivalent complete algorithm for learning the structure of relational models, a more expressive generalization of Bayesian networks. Recent developments in the theory and representation of relational models support lifted reasoning about conditional independence. This enables a powerful constraint for orienting bivariate dependencies and forms the basis of a new algorithm for learning structure. We present the relational causal discovery (RCD) algorithm that learns causal relational models. We prove that RCD is sound and complete, and we present empirical results that demonstrate effectiveness.; Comment: Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013)

Relational models for visual understanding of graphical documents. Application to architectural drawings.

de las Heras, Lluís-Pere
Fonte: [Barcelona] : Universitat Autònoma de Barcelona, Publicador: [Barcelona] : Universitat Autònoma de Barcelona,
Tipo: Tesis i dissertacions electròniques; info:eu-repo/semantics/doctoralThesis; info:eu-repo/semantics/publishedVersion Formato: application/pdf
Publicado em //2015 ENG
Relevância na Pesquisa
46.19%
Els documents gráfics són documents que expressen continguts semántics utilitzant majoritáriament un llenguatge visual. Aquest llenguatge está format per un vocabulari (símbols) i una sintaxi (relacions estructurals entre els símbols) que conjuntament manifesten certs conceptes en un context determinat. Per tant, la interpretació dun document gráfic per part dun ordinador implica tres fases. (1) Ha de ser capadçe detectar automáticament els símbols del document. (2) Ha de ser capadç extreure les relacions estructurals entre aquests símbols. I (3), ha de tenir un model del domini per tal poder extreure la semántica. Exemples de documents gráfics de diferents dominis són els planells darquitectural i d'enginyeria, mapes, diagrames de flux, etc. El Reconeixement de Gráfics, dintre de lárea de recerca de Análisi de Documents, neix de la necessitat de la indústria dinterpretar la gran quantitat de documents gráfics digitalitzats a partir de laparició de lescáner. Tot i que molts anys han passat daquests inicis, el problema de la interpretació automática de documents sembla encara estar lluny de ser solucionat. Básicament, aquest procés sha alentit per una raó principal: la majoria dels sistemes dinterpretació que han estat presentats per la comunitat són molt centrats en una problemática específica...

Application of stochastic models on the portuguese population and distortion to workers conpensation pensioners experience

Nkwenti, Mbelli Njah
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Tipo: Dissertação de Mestrado
Publicado em //2015 ENG
Relevância na Pesquisa
56.09%
Mestrado em Ciências Actuariais; Este estudo resulta de um estágio na AXA, e visa contribuir para a correta determinação das reservas que cobrem os encargos futuros com as indemnizações no Ramo de Acidentes de Trabalho (AT). A questão é muito relevante para as pensões ditas "não obrigatoriamente remíveis", pois a autoridade supervisora (ASF) deixa em parte ao critério das companhias qual o modelo de mortalidade a aplicar. O objetivo do estágio foi assim o desenvolvimento de um modelo estocástico para a mortalidade dos pensionistas em análise, para o que foi necessário considerar inicialmente toda a população portuguesa, passando-se depois para a população constituída pelos trabalhadores cobertos por apólices de AT e, finalmente, para os segurados na AXA. O modelo global é composto por um modelo estocástico para a mortalidade da população e um modelo de mortalidade para o portfólio, obtido a partir de três modelos relacionais (Cox Proportional, Brass Linear and Workgroup PLT). As probabilidades de morte a um ano para as idades 0-110 (período 2013-2113), foram calculadas para a população em geral e para as duas carteiras e utilizadas na construção das correspondentes tábuas de mortalidade e funções associadas. Pôde então determinar-se o montante das reservas relativas aos pensionistas...