Results 1 - 10 of 12,807

Document based modeling of Web services choreographies using Active XML

by Loïc Hélouët, Albert Benveniste
"... Abstract—This paper proposes a document based framework for the modeling of web-based choreographies involving a tight combination of workflow and data management. Our starting point is Active XML proposed by S. Abiteboul — AXML documents are XML documents with embedded service calls. We enhance Act ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
Abstract—This paper proposes a document based framework for the modeling of web-based choreographies involving a tight combination of workflow and data management. Our starting point is Active XML proposed by S. Abiteboul — AXML documents are XML documents with embedded service calls. We enhance

Author manuscript, published in "International conference on Web Services (2010)" Document based modeling of Web services choreographies using Active XML

by Loïc Hélouët, Albert Benveniste , 2011
"... Abstract—This paper proposes a document based framework for the modeling of web-based choreographies involving a tight combination of workflow and data management. Our starting point is Active XML proposed by S. Abiteboul — AXML documents are XML documents with embedded service calls. We enhance Act ..."
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Abstract—This paper proposes a document based framework for the modeling of web-based choreographies involving a tight combination of workflow and data management. Our starting point is Active XML proposed by S. Abiteboul — AXML documents are XML documents with embedded service calls. We enhance

Gradient-based learning applied to document recognition

by Yann Lecun, Léon Bottou, Yoshua Bengio, Patrick Haffner - Proceedings of the IEEE , 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract - Cited by 1533 (84 self) - Add to MetaCart
to deal with the variability of two dimensional (2-D) shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation, recognition, and language modeling. A new learning paradigm, called graph

A Language Modeling Approach to Information Retrieval

by Jay M. Ponte, W. Bruce Croft , 1998
"... Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model. This sugg ..."
Abstract - Cited by 1154 (42 self) - Add to MetaCart
an approach to retrieval based on probabilistic language modeling. We estimate models for each document individually. Our approach to modeling is non-parametric and integrates document indexing and document retrieval into a single model. One advantage of our approach is that collection statistics which

Text Classification from Labeled and Unlabeled Documents using EM

by Kamal Nigam, Andrew Kachites Mccallum, Sebastian Thrun, Tom Mitchell - MACHINE LEARNING , 1999
"... This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. This is important because in many text classification problems obtaining training labels is expensive, while large qua ..."
Abstract - Cited by 1033 (15 self) - Add to MetaCart
quantities of unlabeled documents are readily available. We introduce an algorithm for learning from labeled and unlabeled documents based on the combination of Expectation-Maximization (EM) and a naive Bayes classifier. The algorithm first trains a classifier using the available labeled documents

Latent dirichlet allocation

by David M. Blei, Andrew Y. Ng, Michael I. Jordan, John Lafferty - Journal of Machine Learning Research , 2003
"... We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, ..."
Abstract - Cited by 4365 (92 self) - Add to MetaCart
, in turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of text modeling, the topic probabilities provide an explicit representation of a document. We present efficient approximate inference techniques based on variational methods and an EM algorithm

Probabilistic Latent Semantic Indexing

by Thomas Hofmann , 1999
"... Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized ..."
Abstract - Cited by 1225 (10 self) - Add to MetaCart
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized

A social-cognitive approach to motivation and personality

by Carol S. Dweck, Ellen L. Leggett - Psychological Review , 1988
"... Past work has documented and described major patterns of adaptive and maladaptive behavior: the mastery-oriented and the helpless patterns. In this article, we present a research-based model that accounts for these patterns in terms of underlying psychological processes. The model specifies how indi ..."
Abstract - Cited by 964 (20 self) - Add to MetaCart
Past work has documented and described major patterns of adaptive and maladaptive behavior: the mastery-oriented and the helpless patterns. In this article, we present a research-based model that accounts for these patterns in terms of underlying psychological processes. The model specifies how

The Skill Content of Recent Technological Change: An Empirical Exploration

by David H. Autor, Frank Levy, Richard J. Murnane , 2000
"... Recent empirical and case study evidence documents a strong association between the adoption of computers and increased use of college educated or non-production workers. With few exceptions, the conceptual link explaining how computer technology complements skilled labor or substitutes for unskille ..."
Abstract - Cited by 643 (28 self) - Add to MetaCart
for unskilled labor is less well developed. In this paper, we apply an understanding of what computers do – the execution of procedural or rules-based logic – to develop a simple model of how the widespread adoption of computers in the workplace might alter workplace skill demands. An essential contention

Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes

by Mark E. Crovella, Azer Bestavros , 1996
"... Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a p ..."
Abstract - Cited by 1416 (26 self) - Add to MetaCart
, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity insuch traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in le transfer
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