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Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language

by Philip Resnik , 1999
"... This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The a ..."
Abstract - Cited by 609 (9 self) - Add to MetaCart
This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach

Goal-directed Requirements Acquisition

by Anne Dardenne , Axel van Lamsweerde, Stephen Fickas - SCIENCE OF COMPUTER PROGRAMMING , 1993
"... Requirements analysis includes a preliminary acquisition step where a global model for the specification of the system and its environment is elaborated. This model, called requirements model, involves concepts that are currently not supported by existing formal specification languages, such as goal ..."
Abstract - Cited by 585 (17 self) - Add to MetaCart
, such as goals to be achieved, agents to be assigned, alternatives to be negotiated, etc. The paper presents an approach to requirements acquisition which is driven by such higher-level concepts. Requirements models are acquired as instances of a conceptual meta-model. The latter can be represented as a graph

Markov Random Field Models in Computer Vision

by S. Z. Li , 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
Abstract - Cited by 516 (18 self) - Add to MetaCart
. The latter relates to how data is observed and is problem domain dependent. The former depends on how various prior constraints are expressed. Markov Random Field Models (MRF) theory is a tool to encode contextual constraints into the prior probability. This paper presents a unified approach for MRF modeling

Unsupervised Learning by Probabilistic Latent Semantic Analysis

by Thomas Hofmann - Machine Learning , 2001
"... Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co-occurren ..."
Abstract - Cited by 618 (4 self) - Add to MetaCart
Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co

MIXED MNL MODELS FOR DISCRETE RESPONSE

by Daniel Mcfadden, Kenneth Train - JOURNAL OF APPLIED ECONOMETRICS J. APPL. ECON. 15: 447--470 (2000) , 2000
"... This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as ..."
Abstract - Cited by 487 (15 self) - Add to MetaCart
as closely as one pleases by a MMNL model. Practical estimation of a parametric mixing family can be carried out by Maximum Simulated Likelihood Estimation or Method of Simulated Moments, and easily computed instruments are provided that make the latter procedure fairly efficient. The adequacy of a mixing

Value-Based Software Engineering

by Barry W. Boehm - ACM Software Engineering Notes , 2003
"... Abstract—This paper provides a definition of the term “software engineering ” and a survey of the current state of the art and likely future trends in the field. The survey covers the technology available in the various phases of the software life cycle—requirements engineering, design, coding, test ..."
Abstract - Cited by 472 (32 self) - Add to MetaCart
, test, and maintenance—and in the overall area of software management and integrated technology-management approaches. It is oriented primarily toward discussing the domain of applicability of techniques (where and when they work), rather than how they work in detail. To cover the latter, an extensive

Neuronal Synchrony: A Versatile Code for the Definition of Relations?

by Wolf Singer , 1999
"... temporal relations requires the joint evaluation of responses from more than one neuron, only experiments that permit simultaneous measurements of responses 60528 Frankfurt from multiple units are considered. These include multi-Federal Republic of Germany electrode recordings from multiple individu ..."
Abstract - Cited by 470 (20 self) - Add to MetaCart
in succession. This approach permits as-sessment of event-related variations in discharge rate, but it precludes detection of any covariations in the amplitude or timing of distributed responses if these graphic (MEG) recordings. The signals of these latter

Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches Over Likelihood Ratio Tests

by David Posada, Thomas R. Buckley , 2004
"... Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the sel ..."
Abstract - Cited by 407 (8 self) - Add to MetaCart
selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow

Region Filling and Object Removal by Exemplar-Based Image Inpainting

by A. Criminisi, P. Pérez, K. Toyama , 2004
"... A new algorithm is proposed for removing large objects from digital images. The challenge is to fill in the hole that is left behind in a visually plausible way. In the past, this problem has been addressed by two classes of algorithms: 1) “texture synthesis” algorithms for generating large image re ..."
Abstract - Cited by 365 (1 self) - Add to MetaCart
regions from sample textures and 2) “inpainting ” techniques for filling in small image gaps. The former has been demonstrated for “textures”—repeating twodimensional patterns with some stochasticity; the latter focus on linear “structures ” which can be thought of as one-dimensional patterns

Posterior Predictive Assessment of Model Fitness Via Realized Discrepancies

by Andrew Gelman, Xiao-li Meng, Hal Stern - Statistica Sinica , 1996
"... Abstract: This paper considers Bayesian counterparts of the classical tests for goodness of fit and their use in judging the fit of a single Bayesian model to the observed data. We focus on posterior predictive assessment, in a framework that also includes conditioning on auxiliary statistics. The B ..."
Abstract - Cited by 348 (39 self) - Add to MetaCart
. The Bayesian formulation facilitates the construction and calculation of a meaningful reference distribution not only for any (classical) statistic, but also for any parameter-dependent “statistic ” or discrepancy. The latter allows us to propose the realized discrepancy assessment of model fitness, which
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