Distribution modelling

Xem 1-20 trên 958 kết quả Distribution modelling
  • A major focus of current work in distributional models of semantics is to construct phrase representations compositionally from word representations. However, the syntactic contexts which are modelled are usually severely limited, a fact which is reflected in the lexical-level WSD-like evaluation methods used.

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  • Frequency distribution models tuned to words and other linguistic events can predict the number of distinct types and their frequency distribution in samples of arbitrary sizes. We conduct, for the first time, a rigorous evaluation of these models based on cross-validation and separation of training and test data. Our experiments reveal that the prediction accuracy of the models is marred by serious overfitting problems, due to violations of the random sampling assumption in corpus data. We then propose a simple pre-processing method to alleviate such non-randomness problems. ...

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  • Information Systems are the software and hardware systems that support dataintensive applications. One of the most critical stages of an Information System development cycle is the System Design stage. During this stage the architecture, components, modules, interfaces and system data are defined and modeled in order to fulfill the respective requirements that the developed Information System should meet.

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  • Tham khảo luận văn - đề án 'báo cáo lâm nghiệp: "a linkage among whole-stand model, individual-tree model and diameter-distribution model"', luận văn - báo cáo phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: The Washington Needle Depot: fitting healthcare to injection drug users rather than injection drug users to healthcare: moving from a syringe exchange to syringe distribution model

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  • Our research aims at building computational models of word meaning that are perceptually grounded. Using computer vision techniques, we build visual and multimodal distributional models and compare them to standard textual models. Our results show that, while visual models with state-of-the-art computer vision techniques perform worse than textual models in general tasks (accounting for semantic relatedness), they are as good or better models of the meaning of words with visual correlates such as color terms, even in a nontrivial task that involves nonliteral uses of such words. ...

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  • This paper describes ongoing work on distributional models for word meaning in context. We abandon the usual one-vectorper-word paradigm in favor of an exemplar model that activates only relevant occurrences. On a paraphrasing task, we find that a simple exemplar model outperforms more complex state-of-the-art models.

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  • Distributional similarity is a useful notion in estimating the probabilities of rare joint events. It has been employed both to cluster events according to their distributions, and to directly compute averages of estimates for distributional neighbors of a target event. Here, we examine the tradeoffs between model size and prediction accuracy for cluster-based and nearest neighbors distributional models of unseen events.

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  • We present a generative distributional model for the unsupervised induction of natural language syntax which explicitly models constituent yields and contexts. Parameter search with EM produces higher quality analyses than previously exhibited by unsupervised systems, giving the best published unsupervised parsing results on the ATIS corpus. Experiments on Penn treebank sentences of comparable length show an even higher F1 of 71% on nontrivial brackets. We compare distributionally induced and actual part-of-speech tags as input data, and examine extensions to the basic model.

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  • Following Link [14, 13] and Roberts [15], I present a semantic analysis of collective- distributivity comes from either an explicit quantifidistributive ambiguity, and resolution of such am- cational operator like each or an implicit distributive biguity by model-based reasoning. This approach operator called the D o p e r a t o r . The D operator goes beyond Scha and Stallard [17], whose reasoning was motivated by the equivalence in the semantics capability was limited to checking semantic types. of the following sentences.

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  • In industrialized countries, distribution systems deliver electricity literally everywhere, taking power generated at many locations and delivering it to end users. Generation, transmission, and distribution — of these big three components of the electricity infrastructure, the distribution system gets the least attention. Yet, it is often the most critical component in terms of its effect on reliability and quality of service, cost of electricity, and aesthetic (mainly visual) impacts on society....

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  • The final article in this section presents a modification to the Green’s function approach for modeling acoustic pressure, where the use of conformal mapping is replaced by a group of bound vortices. The author shows that the approach is readily extended to three dimensions. The method is discussed in the context of aircraft noise.

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  • Ecotoxicological models have been applied increasingly to perform chemical risk assessments since the first models of this kind emerged about 25 years ago. The first ecotoxicological models were applied to very specific cases — for instance, cadmium contamination of Lake Erie or mercury contamination of Mex Bay, Alexandria. The models were inspired by the experience gained in ecological modeling and therefore contained good descriptions of ecological processes. Slightly later, the so-called fate models emerged, which were first developed by McKay and others.

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  • Kersting, William H. “Distribution Systems” The Electric Power Engineering Handbook Ed. L.L. Grigsby Boca Raton: CRC Press LLC, 2001 Distribution Systems William H. Kersting New Mexico State University 6.1 Power System Loads Raymond R. Shoults and Larry D. Swift 6.2 Distribution System Modeling and Analysis William H. Kersting 6.3 Power System Operation and Control George L. Clark and Simon W. Bowe.6 Distribution Systems Raymond R.

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  • Modeling Hydrologic Change: Statistical Methods is about modeling systems where change has affected data that will be used to calibrate and test models of the systems and where models will be used to forecast system responses after change occurs. The focus is not on the hydrology. Instead, hydrology serves as the discipline from which the applications are drawn to illustrate the principles of modeling and the detection of change. All four elements of the modeling process are discussed: conceptualization, formulation, calibration, and verification.

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  • The definition of a distributed system (1) A distributed system is: A collection of independent computers appears to its user as a single combine thong.Mot distribution system organized as middleware. Note that the intermediate layer extended over multiple computers.

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  • For the past 14 years, Professor Ann Harding has spearheaded the devel- opment of highly sophisticated microsimulation models and databases within Australia, so that policy makers can gain much better information about the likely distributional impact of current and proposed policies. She leads the University of Canberra’s National Centre for Social and Economic Modelling, established in January 1993, and is a professor of Applied Eco- nomics and Social Policy at the University.

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  • SERVICE PARTS LOGISTICS: MODELING, ANALYSIS AND APPLICATION Chapter One develops this idea and implements tests of the hypothesis that school effectiveness is an important determinant of residential choices among local-monopoly school districts. I model a “Tiebout”-style housing market in which house prices ration access to desirable schools, which may be desirable either because they are particularly effective or because they enroll a desirable set of students.

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  • Tham khảo sách 'modelling with autocad 2012', kỹ thuật - công nghệ, tự động hoá phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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