scholarly journals An equivalence-preserving CPS translation via multi-language semantics

2011 ◽  
Author(s):  
Amal Ahmed ◽  
Matthias Blume
Keyword(s):  
Language Semantics

What is—or, for that Matter, isn’t—‘Experimental’ Semantics?

2018 ◽  
Author(s):  
Pauline Jacobson
Keyword(s):  
Natural Language ◽  
Large Scale ◽  
Empirical Work ◽  
Thought Experiments ◽  
Natural Language Semantics ◽  
Empirical Methods ◽  
Language Semantics ◽  
Experimental Semantics

This chapter examines the currently fashionable notion of ‘experimental semantics’, and argues that most work in natural language semantics has always been experimental. The oft-cited dichotomy between ‘theoretical’ (or ‘armchair’) and ‘experimental’ is bogus and should be dropped form the discourse. The same holds for dichotomies like ‘intuition-based’ (or ‘thought experiments’) vs. ‘empirical’ work (and ‘real experiments’). The so-called new ‘empirical’ methods are often nothing more than collecting the large-scale ‘intuitions’ or, doing multiple thought experiments. Of course the use of multiple subjects could well allow for a better experiment than the more traditional single or few subject methodologies. But whether or not this is the case depends entirely on the question at hand. In fact, the chapter considers several multiple-subject studies and shows that the particular methodology in those cases does not necessarily provide important insights, and the chapter argues that some its claimed benefits are incorrect.

A Metalogical Theory of Natural Language Semantics

2005 ◽  
Vol 28 (1) ◽  
pp. 73-116
Author(s):  
Michael Mccord ◽  
Arendse Bernth
Keyword(s):  
Natural Language ◽  
Natural Language Semantics ◽  
Language Semantics

scholarly journals Preface

2015 ◽  
Vol 27 (4) ◽  
pp. 459-459
Author(s):  
ACHIM JUNG ◽  
GUO-QIANG ZHANG
Keyword(s):  
Lattice Theory ◽  
Process Algebra ◽  
Metric Spaces ◽  
Domain Theory ◽  
Conference Series ◽  
The Third ◽  
Language Semantics ◽  
And Mathematics ◽  
October 17 ◽  
Partial Logics

The International Symposium on Domain Theory (ISDT) is a conference series intended to be a forum for researchers in domain theory and its applications. Topics include topological and logical aspects of domains; categories of domains and powerdomains; continuous posets and their representations; partial orders, lattice theory and metric spaces; types, process algebra and concurrency; non-classical and partial logics; programming language semantics; applications in computer science and mathematics. This conference series was founded by Yingming Liu, Yixiang Chen, Klaus Keimel, and Guo-Qiang Zhang. All ISDT events have taken place in China. The first ISDT was held in Shanghai, October 17–24, 1999; the second ISDT was held in Chengdu, October 22–26, 2001; the third ISDT occurred in Xi'an, China, May 10–14, 2004; the fourth ISDT was held in Changsha, June 2–6, 2006; and the fifth ISDT took place in Shanghai, September 11–14, 2009.

Special Issue: Quantum structures in computer science: Language, semantics, retrieval

2018 ◽  
Vol 752 ◽  
pp. 1-4 ◽  
Author(s):  
Diederik Aerts ◽  
Massimo Melucci ◽  
Massimiliano Sassoli de Bianchi ◽  
Sandro Sozzo ◽  
Tomas Veloz
Keyword(s):  
Computer Science ◽  
Quantum Structures ◽  
Special Issue ◽  
Language Semantics

scholarly journals Language Semantics Interpretation with an Interaction-Based Recurrent Neural Network

2021 ◽  
Vol 3 (4) ◽  
pp. 922-945
Author(s):  
Shaw-Hwa Lo ◽  
Yiqiao Yin
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Language Processing ◽  
Text Classification ◽  
Search Algorithm ◽  
Greedy Search ◽  
Text Documents ◽  
Engineering Technique ◽  
Language Semantics ◽  
Sequential Models

Text classification is a fundamental language task in Natural Language Processing. A variety of sequential models are capable of making good predictions, yet there is a lack of connection between language semantics and prediction results. This paper proposes a novel influence score (I-score), a greedy search algorithm, called Backward Dropping Algorithm (BDA), and a novel feature engineering technique called the “dagger technique”. First, the paper proposes to use the novel influence score (I-score) to detect and search for the important language semantics in text documents that are useful for making good predictions in text classification tasks. Next, a greedy search algorithm, called the Backward Dropping Algorithm, is proposed to handle long-term dependencies in the dataset. Moreover, the paper proposes a novel engineering technique called the “dagger technique” that fully preserves the relationship between the explanatory variable and the response variable. The proposed techniques can be further generalized into any feed-forward Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs), and any neural network. A real-world application on the Internet Movie Database (IMDB) is used and the proposed methods are applied to improve prediction performance with an 81% error reduction compared to other popular peers if I-score and “dagger technique” are not implemented.

scholarly journals Jugendliterarische Werke im interkulturellen, medienintegrativen Litertaturunterricht

2018 ◽  
Vol 45 (1) ◽  
pp. 85-104
Author(s):  
Ksenia Kuzminykh
Keyword(s):  
Language Teaching ◽  
Teaching Model ◽  
Literary Language ◽  
Language Semantics ◽  
Theories Of Reading ◽  
And Performance ◽  
Media Learning ◽  
Literature And Film

The article starts with a discussion of the essential theories of reading and focuses on different models of understanding. In the next step, based on fragments taken from a novel by M. Zusak, the article develops an integrative literary and language teaching model in intercultural school lessons of literature in a way which stimulates a highly functional analytical, receptive and productive handling of language semantics and performance. It demonstrates the combination of literature and film as a possibility for successful literary, language and media learning.

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