Models for data
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“ A Developer’s Guide to Data Modeling for SQL Server explains the concepts and practice of data modeling with a clarity that makes the technology accessible to anyone building databases and data-driven applications. “Eric Johnson and Joshua Jones combine a deep understanding of the science of data modeling with the art that comes with years of experience. If you’re new to data modeling, or find the need to brush up on its concepts, this book is for you.” —Peter Varhol, Executive Editor, Redmond Magazine ...
299p
ringphone
06-05-2013
29
9
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We address the problem of selecting nondomain-specific language model training data to build auxiliary language models for use in tasks such as machine translation. Our approach is based on comparing the cross-entropy, according to domainspecific and non-domain-specifc language models, for each sentence of the text source used to produce the latter language model. We show that this produces better language models, trained on less data, than both random data selection and two other previously proposed methods. ...
5p
hongdo_1
12-04-2013
20
2
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Lecture "Advanced Econometrics (Part II) - Chapter 6: Models for count data" presentation of content: Poisson regression model, goodness of fit, overdispersion, negative binomial regression model, too many zeros data.
7p
nghe123
06-05-2016
20
2
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This book is intended to introduce environmental scientists and managers to the statistical methods that will be useful for them in their work. A secondary aim was to produce a text suitable for a course in statistics for graduate students in the environmental science area. I wrote the book because it seemed to me that these groups should really learn about statistical methods in a special way. It is true that their needs are similar in many respects to those working in other areas.
285p
crazy_sms
10-05-2012
104
43
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This Second Edition of the go-to reference combines the classical analysis and modern applications of applied mathematics for chemical engineers. The book introduces traditional techniques for solving ordinary differential equations (ODEs), adding new material on approximate solution methods such as perturbation techniques and elementary numerical solutions. It also includes analytical methods to deal with important classes of finite-difference equations. The last half discusses numerical solution techniques and partial differential equations (PDEs). The read...
0p
la_la123
05-04-2013
37
9
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IBML Data Modeling Techniques for Data Warehousing Chuck Ballard, Dirk Herreman, Don Schau, Rhonda Bell, Eunsaeng Kim, Ann Valencic International Technical Support Organization http://www.redbooks.ibm.com SG24-2238-00 ..IBML International Technical Support Organization SG24-2238-00 Data Modeling Techniques for Data Warehousing February 1998 .Take Note! Before using this information and the product it supports, be sure to read the general information in Appendix B, “Special Notices” on page 183.
216p
ptng13
17-05-2012
36
4
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We present a global joint model for lemmatization and part-of-speech prediction. Using only morphological lexicons and unlabeled data, we learn a partiallysupervised part-of-speech tagger and a lemmatizer which are combined using features on a dynamically linked dependency structure of words. We evaluate our model on English, Bulgarian, Czech, and Slovene, and demonstrate substantial improvements over both a direct transduction approach to lemmatization and a pipelined approach, which predicts part-of-speech tags before lemmatization. ...
9p
hongphan_1
14-04-2013
22
3
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Morphological processes in Semitic languages deliver space-delimited words which introduce multiple, distinct, syntactic units into the structure of the input sentence. These words are in turn highly ambiguous, breaking the assumption underlying most parsers that the yield of a tree for a given sentence is known in advance. Here we propose a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity.
9p
hongphan_1
15-04-2013
21
3
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The applicability of many current information extraction techniques is severely limited by the need for supervised training data. We demonstrate that for certain field structured extraction tasks, such as classified advertisements and bibliographic citations, small amounts of prior knowledge can be used to learn effective models in a primarily unsupervised fashion. Although hidden Markov models (HMMs) provide a suitable generative model for field structured text, general unsupervised HMM learning fails to learn useful structure in either of our domains.
8p
bunbo_1
17-04-2013
23
3
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In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect training data. The Multi-Class Composite N-gram maintains an accurate word prediction capability and reliability for sparse data with a compact model size based on multiple word clusters, called MultiClasses. In the Multi-Class, the statistical connectivity at each position of the N-grams is regarded as word attributes, and one word cluster each is created to represent the positional attributes. ...
8p
bunrieu_1
18-04-2013
36
3
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We propose a novel reordering model for phrase-based statistical machine translation (SMT) that uses a maximum entropy (MaxEnt) model to predicate reorderings of neighbor blocks (phrase pairs). The model provides content-dependent, hierarchical phrasal reordering with generalization based on features automatically learned from a real-world bitext. We present an algorithm to extract all reordering events of neighbor blocks from bilingual data.
8p
hongvang_1
16-04-2013
24
2
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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.
8p
bunmoc_1
20-04-2013
14
2
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EUFID is a natural language frontend for data management systems. It is modular and table driven so that it can be interfaced to different applications and data management systems. It allows a user to query his data base in natural English, including sloppy syntax and misspellings. The tables contain a data management system view of the data base, a semantic/syntactic view of the application, and a mapping from the second to the first. We are entering a new era in data base access. Computers and terminals have come down in price while salaries have risen. ...
4p
bungio_1
03-05-2013
21
2
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Lecture "Advanced Econometrics (Part II) - Chapter 10: Models for panel data" presentation of content: General framework for panel data, pooled regression, fixed effects, random effects model, choosing between fixed and random effects models, finding big.
0p
nghe123
06-05-2016
19
2
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Chapter 6 - Developing data models for business databases. Chapter 5 explained the Crow's Foot notation for entity relationship diagrams. You learned about diagram symbols, relationship patterns, generalization hierarchies, and rules for consistency and completeness. Understanding the notation is a prerequisite for applying it to represent business databases. This chapter explains the development of data models for business databases using the Crow's Foot notation and rules to convert ERDs to table designs.
38p
nomoney1
10-02-2017
6
2
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The traditional mention-pair model for coreference resolution cannot capture information beyond mention pairs for both learning and testing. To deal with this problem, we present an expressive entity-mention model that performs coreference resolution at an entity level. The model adopts the Inductive Logic Programming (ILP) algorithm, which provides a relational way to organize different knowledge of entities and mentions.
9p
hongphan_1
15-04-2013
15
1
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Module 9 - Creating a security design for data. In this module, you will learn how to determine threats and analyze risks to data in an organization. You will learn how to design an access control model for files and folders in order to protect data that is stored on network servers. You will also learn about considerations for encrypting and managing data.
16p
nomoney2
10-02-2017
9
1
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(BQ) In this paper, an easily implemented method is developed to describe the variations of EDM process, represented by gap states. On the basis of a time series of gap states from a machining process, the paper first studied a general descriptive model for EDM process, and then equivalently simplified the model for application; after spectral analysis, preprocessing of data, parameters selection and model validation proposed a well-defined model. Finally, by using this model structure and size, an online time-varied predictive model was developed.
10p
xuanphuongdhts
27-03-2017
3
1
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This paper proposes a 2D-quasi model for simulations of the lateral distribution of flow velocity and of unit water discharge in open-channel sections. The latters are obtained by solving the governing equation, which is derived from the Reynolds equations and allows for taking into account the gravity, bed shear stress, and turbulent diffusion force in calculations. Using the experimental data, a sensitivity analysis of modeling parameters, e.g. Manning coefficient and eddy viscosity was performed firstly.
8p
thihuynh3006
16-03-2018
0
0
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4.2.3 MTMF MTMF combines the best parts of the Linear Spectral Mixing model and the statistical Matched Filter model while avoiding the drawbacks of each parent method (Boardman, 1998). It is a useful Matched Filter method without knowing all the possible endmembers in a landscape especially in case of subtle, sub-pixel occurrences. Firstly, pixel spectra and endmember spectra require a minimum noise fraction (MNF) (Green et al., 1988, Boardman, 1993) transformation. MNF reduces and separates an image into its most dimensional and non-noisy components.
464p
lulanphuong
22-03-2012
122
40
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