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Classifier Structures in Mandarin Chinese, Niina Ning Zhang


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Автор: Niina Ning Zhang
Название:  Classifier Structures in Mandarin Chinese
ISBN: 9783110303742
Издательство: Walter de Gruyter
Классификация:

ISBN-10: 3110303744
Обложка/Формат: Hardback
Страницы: 331
Вес: 0.57 кг.
Дата издания: 21.05.2013
Серия: Trends in linguistics. studies and monographs [tilsm]
Язык: English
Иллюстрации: 80 tables, black and white; 40 illustrations, black and white
Размер: 231 x 163 x 25
Читательская аудитория: Professional and scholarly
Ключевые слова: Grammar, syntax & morphology, LANGUAGE ARTS & DISCIPLINES / Linguistics / General
Основная тема: LANGUAGE ARTS & DISCIPLINES / Linguistics / General
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This monograph addresses fundamental syntactic issues of classifier constructions, based on a thorough study of a typical classifier language, Mandarin Chinese. It shows that the contrast between count and mass is not binary. Instead, there are two independently attested features: Numerability, the ability of a noun to combine with a numeral directly, and Delimitability, the ability of a noun to be modified by a delimitive modifier, such as size, shape, or boundary modifier. Although all nouns in Chinese are non-count nouns, there is still a mass/non-mass contrast, with mass nouns selected by individuating classifiers and non-mass nouns selected by individual classifiers. Some languages have the counterparts of Chinese individuating classifiers only, some languages have the counterparts of Chinese individual classifiers only, and some other languages have no counterpart of either individual or individuating classifiers of Chinese. The book also reports that unit plurality can be expressed by reduplicative classifiers in the language. Moreover, for the constituency of a numeral expression, an individual, individuating, or kind classifier combines with the noun first and then the numeral is integrated; but a partitive or collective classifier, like a measure word, combines with the numeral first, before the noun is integrated into the whole nominal structure. Furthermore, the book identifies the syntactic positions of various uses of classifiers in the language. A classifier is at a functional head position that has a dependency with a numeral, or a position that has a dependency with a generic or existential quantifier, or a position that represents the singular-plural contrast, or a position that licenses a delimitive modifier when the classifier occurs in a compound.


Learning Classifier Systems

Автор: Jaume Bacardit; Ester Bernad?-Mansilla; Martin V.
Название: Learning Classifier Systems
ISBN: 3540881379 ISBN-13(EAN): 9783540881377
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Covers post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - hosted by the Genetic and Evolutionary Computation Conference, GECCO. This book features sections on knowledge representation, and analysis of the system.

Multiple Classifier Systems

Автор: Neamat El Gayar; Josef Kittler; Fabio Roli
Название: Multiple Classifier Systems
ISBN: 3642121268 ISBN-13(EAN): 9783642121265
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Constitutes the proceedings of the 9th International Workshop on Multiple Classifier Systems, MCS 2010, held in Cairo, Egypt, in April 2010. This book includes contributions that are organized into sessions dealing with classifier combination and classifier selection, diversity, bagging and boosting, and combination of multiple kernels.

Multiple Classifier Systems

Автор: J?n Atli Benediktsson; Josef Kittler; Fabio Roli
Название: Multiple Classifier Systems
ISBN: 3642023258 ISBN-13(EAN): 9783642023255
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009. This work contains papers that are organized in topical sections on ECOC boosting and bagging, MCS in remote sensing, unbalanced data and decision templates, concept drift and SVM ensembles.

Learning Classifier Systems

Автор: Tim Kovacs; Xavier Llor?; Keiki Takadama; Pier Luc
Название: Learning Classifier Systems
ISBN: 3540712305 ISBN-13(EAN): 9783540712305
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Constitutes the refereed joint post-proceedings of 3 consecutive International Workshops on Learning Classifier Systems that took place in Chicago, IL, USA in July 2003, in Seattle, WA, USA in June 2004, and in Washington, DC, USA in June 2005 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.

Multiple Classifier Systems

Автор: Nikunj C. Oza; Robi Polikar; Josef Kittler; Fabio
Название: Multiple Classifier Systems
ISBN: 3540263063 ISBN-13(EAN): 9783540263067
Издательство: Springer
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Цена: 13275.00 р.
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Описание: Constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. This book contains papers that are organized in topical sections on boosting, combination methods, performance analysis, and applications. They exemplify the advances in the theory and applications of multiple classifier systems.


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