Download or read book The Classification Program written by Philip Hunter DuBois and published by . This book was released on 1947 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Introduction to C Algebras and the Classification Program written by Karen R. Strung and published by Springer Nature. This book was released on 2020-12-15 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is directed towards graduate students that wish to start from the basic theory of C*-algebras and advance to an overview of some of the most spectacular results concerning the structure of nuclear C*-algebras. The text is divided into three parts. First, elementary notions, classical theorems and constructions are developed. Then, essential examples in the theory, such as crossed products and the class of quasidiagonal C*-algebras, are examined, and finally, the Elliott invariant, the Cuntz semigroup, and the Jiang-Su algebra are defined. It is shown how these objects have played a fundamental role in understanding the fine structure of nuclear C*-algebras. To help understanding the theory, plenty of examples, treated in detail, are included. This volume will also be valuable to researchers in the area as a reference guide. It contains an extensive reference list to guide readers that wish to travel further.

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Download or read book Software Similarity and Classification written by Silvio Cesare and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software similarity and classification is an emerging topic with wide applications. It is applicable to the areas of malware detection, software theft detection, plagiarism detection, and software clone detection. Extracting program features, processing those features into suitable representations, and constructing distance metrics to define similarity and dissimilarity are the key methods to identify software variants, clones, derivatives, and classes of software. Software Similarity and Classification reviews the literature of those core concepts, in addition to relevant literature in each application and demonstrates that considering these applied problems as a similarity and classification problem enables techniques to be shared between areas. Additionally, the authors present in-depth case studies using the software similarity and classification techniques developed throughout the book.

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Download or read book Handbook of Diagnostic Classification Models written by Matthias von Davier and published by Springer Nature. This book was released on 2019-10-11 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification. The handbook also offers applications and special topics and practical guidelines how to plan and conduct research studies with the help of DCMs. Commonly used models in educational measurement and psychometrics typically assume a single latent trait or at best a small number of latent variables that are aimed at describing individual differences in observed behavior. While this allows simple rankings of test takers along one or a few dimensions, it does not provide a detailed picture of strengths and weaknesses when assessing complex cognitive skills. DCMs, on the other hand, allow the evaluation of test taker performance relative to a potentially large number of skill domains. Most diagnostic models provide a binary mastery/non-mastery classification for each of the assumed test taker attributes representing these skill domains. Attribute profiles can be used for formative decisions as well as for summative purposes, for example in a multiple cut-off procedure that requires mastery on at least a certain subset of skills. The number of DCMs discussed in the literature and applied to a variety of assessment data has been increasing over the past decades, and their appeal to researchers and practitioners alike continues to grow. These models have been used in English language assessment, international large scale assessments, and for feedback for practice exams in preparation of college admission testing, just to name a few. Nowadays, technology-based assessments provide increasingly rich data on a multitude of skills and allow collection of data with respect to multiple types of behaviors. Diagnostic models can be understood as an ideal match for these types of data collections to provide more in-depth information about test taker skills and behavioral tendencies.

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