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【每日书讯】Mass and Count in Linguistics, Philosophy, and Cognitive Science等3则书讯

302 阅读 128 下载 2021-06-02 12:42:28 上传 7.6 MB

今日推出2则书讯:①2021年最新专著Mass and Count in Linguistics, Philosophy, and Cognitive Science;②2021年最新专著Things and Stuff: The Semantics of the Count-Mass Distinction;③2020年前沿新著Emotion and Cause: Linguistic Theory and Computational Implementation

Mass and Count in Linguistics, Philosophy, and Cognitive Science等3则书讯



今日推出2则书讯:

①2021年最新专著Mass and Count in Linguistics, Philosophy, and Cognitive Science

②2021年最新专著Things and Stuff: The Semantics of the Count-Mass Distinction

欲获取更多关于此书的资讯,请添加“语言学小电”的微信13764179404进行咨询!


③2020年前沿新著Emotion and Cause: Linguistic Theory and Computational Implementation



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【书名】:Mass and Count in Linguistics, Philosophy, and Cognitive Science

【作者】:Friederike Moltmann (ed.)

【年份】:2021

【简介】:关于可数与不可数(物质名词)的研究的两本最新论文集

The mass-count distinction is a morpho-syntactic distinction among nouns that is generally taken to have semantic content. This content is generally taken to reflect a conceptual, cognitive, or ontological distinction and relates to philosophical and cognitive notions of unity, identity, and counting. The mass-count distinction is certainly one of the most interesting and puzzling topics in syntax and semantics that bears on ontology and cognitive science. In many ways, the topic remains under-researched, though, across languages and with respect to particular phenomena within a given language, with respect to its connection to cognition, and with respect to the way it may be understood ontologically. This volume aims to contribute to some of the gaps in the research on the topic, in particular the relation between the syntactic mass-count distinction and semantic and cognitive distinctions, diagnostics for mass and count, the distribution and role of numeral classifiers, abstract mass nouns, and object mass nouns (furniture, police force, clothing).

此书讯“语言学小电”提供,感兴趣可添加“语言学小电”的微信13764179404进行咨询!

【书名】:Things and Stuff: The Semantics of the Count-Mass Distinction

【作者】:Tibor Kiss et al. (eds.)

【年份】:2021

【简介】:关于可数与不可数(物质名词)的研究的两本最新论文集

A classical viewpoint claims that reality consists of both things and stuff, and that we need a way to discuss these aspects of reality. This is achieved by using +count terms to talk about things while using +mass terms to talk about stuff. Bringing together contributions from internationally-renowned experts across interrelated disciplines, this book explores the relationship between mass and count nouns in a number of syntactic environments, and across a range of languages. It both explains how languages differ in their methods for describing these two fundamental categories of reality, and shows the many ways that modern linguistics looks to describe them. It also explores how the notions of count and mass apply to 'abstract nouns', adding a new dimension to the countability discussion. With its pioneering approach to the fundamental questions surrounding mass-count distinction, this book will be essential reading for researchers in formal semantics and linguistic typology.

【书名】:Emotion and Cause: Linguistic Theory and Computational Implementation

【作者】:Sophia Yat Mei Lee

【年份】:2020

【简介】:This work argues that cause events, being the most tangible component of emotion, provide a rich dimension of how emotions should be classified. While it is often claimed that emotional concepts cannot be defined, this work views emotion as a response triggered by actual or perceived events, specifically focusing on the interaction between five primary emotions (Happiness, Sadness, Fear, Anger, and Surprise) and cause events. Cause events are examined in terms of two dimensions, namely transitivity and epistemicity. By incorporating the semantic and syntactic information of emotion cause events, this representation of emotion not only provides deep linguistic criteria of emotion cause events, but also offers an event-based approach to emotion classification. A text-driven, rule-based system for detecting the causes of emotion is then developed to establish the validity of the proposed linguistic model for emotion detection and classification. The system shows promising results.

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