Semantic Organization Development of Chinese Preschool Children from a Dynamic Semantic Network Perspective

2021 ◽  
Author(s):  
Xiaohui Bai ◽  
Jianpeng Liu
Keyword(s):  
Preschool Children ◽  
Organization Development ◽  
Semantic Network ◽  
Dynamic Semantic ◽  
Semantic Organization

scholarly journals Statistical Regularities Shape Semantic Organization throughout Development

2020 ◽  
Author(s):  
Layla Unger ◽  
Olivera Savic ◽  
Vladimir Sloutsky
Keyword(s):  
Semantic Network ◽  
Cued Recall ◽  
Visual World Paradigm ◽  
Stable Category ◽  
Semantic Organization ◽  
Taxonomic Relatedness ◽  
The World ◽  
Semantic Development ◽  
Statistical Regularities ◽  
Taxonomic Relations

Our knowledge about the world is represented not merely as a collection of concepts, but as an organized lexico-semantic network in which concepts can be linked by relations, such as “taxonomic” relations between members of the same stable category (e.g., cat and sheep), or association between entities that occur together or in the same context (e.g., sock and foot). To date, accounts of the origins of semantic organization have largely overlooked how sensitivity to statistical regularities ubiquitous in the environment may play a powerful role in shaping semantic development. The goal of the present research was to investigate how associations in the form of statistical regularities with which labels for concepts co-occur in language (e.g., sock and foot) and taxonomic relatedness (e.g., sock and pajamas) shape semantic organization of 4-5-year-olds and adults. To examine these aspects of semantic organization across development, we conducted three experiments examining effects of co-occurrence and taxonomic relatedness on cued recall (Experiment 1), word-picture matching (Experiment 2), and looking dynamics in a Visual World paradigm (Experiment 3). Taken together, the results of the three experiments provide evidence that co-occurrence-based links between concepts manifest in semantic organization from early childhood onward, and are increasingly supplemented by taxonomic links. We discuss these findings in relation to theories of semantic development.

Feature Model Design Using Dynamic Feature Semantic Network

2011 ◽  
Vol 55-57 ◽  
pp. 1263-1268
Author(s):  
Yong Tao Hao ◽  
Si Zhen Peng
Keyword(s):  
Semantic Network ◽  
Feature Model ◽  
Dynamic Feature ◽  
Model Design ◽  
Practical Application ◽  
Dynamic Semantic ◽  
Manufacturing Information ◽  
Feature Technology ◽  
Construct System

In order to improve practical application of feature technology, feature operators are defined to describe feature manufacturing information, which is added into semantic network to construct a dynamic semantic network. As designed by feature by model could store feature type and feature relationship information, it is used in the construction of dynamic feature semantic network. At last, the example shows that the proposed semantic network construct system could work well.

scholarly journals Semantic Studies of Organisation and Functioning of Mental Lexicon

2020 ◽  
Vol 1 (8) ◽  
pp. 29-51
Author(s):  
V. A. Belov
Keyword(s):  
Semantic Network ◽  
Mental Lexicon ◽  
Small World ◽  
Sources Of Information ◽  
Word Similarity ◽  
Spatial Metaphor ◽  
Semantic Organization ◽  
Advantages And Disadvantages ◽  
Leading Position ◽  
Semantic Proximity

 The review article discusses the key problems of semantic organization of the mental lexicon. It is understood as a dynamic, cognitively organized semantic network of lexical units. The paper presents the characteristics of the main models of semantic organization of mental vocabulary, highlights the advantages and disadvantages of each approach. It is noted that currently connectionist models are developing most actively. Among them there are the following: the small world network, which considers a certain fragment of the lexicon; thesaurus models that combine all units of the lexicon; computational and distributive models that build relationships between a large number of units based on corpus data about shared usage. The author analyses the sources of information about the organization of the mental lexicon, among which the leading position is occupied by the results of associative experiments and priming. It is revealed that research is also carried out on the subjects’ intuitive assessments of word similarity, analysis of unintentional speech errors. Neuropsychological technologies are used to study the mental lexicon. The problem of semantic relations in the mental lexicon, which are described using a “spatial” metaphor, is discussed separately: semantic proximity is considered as a distance or a vector.

scholarly journals Fast Distributed Dynamics of Semantic Networks via Social Media

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Facundo Carrillo ◽  
Guillermo A. Cecchi ◽  
Mariano Sigman ◽  
Diego Fernández Slezak
Keyword(s):  
Social Media ◽  
Semantic Network ◽  
Semantic Networks ◽  
High Temporal Resolution ◽  
Semantic Similarity Measure ◽  
Semantic Relationships ◽  
Distributed Structure ◽  
Semantic Organization ◽  
The Social ◽  
Induced Changes

We investigate thedynamicsof semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network.

scholarly journals The Emergence of Richly Organized Semantic Knowledge from Simple Statistics: A Synthetic Review

2021 ◽  
Author(s):  
Layla Unger ◽  
Anna Fisher
Keyword(s):  
Computational Modeling ◽  
Statistical Learning ◽  
Semantic Network ◽  
Semantic Knowledge ◽  
Future Research ◽  
Unexpected Events ◽  
Semantic Organization ◽  
The World ◽  
Semantic Concepts ◽  
Statistical Regularities

As adults, we draw upon our ample knowledge about the world to support such vital cognitive feats as using language, reasoning, retrieving knowledge relevant to our current goals, planning for the future, adapting to unexpected events, and navigating through the environment. Our knowledge readily supports these feats because it is not merely a collection of stored facts, but rather functions as an organized, semantic network of concepts connected by meaningful relations. How do the relations that fundamentally organize semantic concepts emerge with development? Here, we cast a spotlight on a potentially powerful but often overlooked driver of semantic organization: Rich statistical regularities that are ubiquitous in both language and visual input. In this synthetic review, we show that a driving role for statistical regularities is convergently supported by evidence from diverse fields, including computational modeling, statistical learning, and semantic development. Finally, we identify a number of key avenues of future research into how statistical regularities may drive the development of semantic organization.

scholarly journals Evidence for a deep, distributed and dynamic semantic code in human ventral anterior temporal cortex

2019 ◽  
Author(s):  
Timothy T. Rogers ◽  
Christopher Cox ◽  
Qihong Lu ◽  
Akihiro Shimotake ◽  
Takayuki Kikuch ◽  
...  
Keyword(s):  
Semantic Information ◽  
Semantic Network ◽  
Temporal Cortex ◽  
Semantic Features ◽  
Dynamic Semantic ◽  
Temporal Lobes ◽  
Neural Populations ◽  
Ventral Temporal Cortex ◽  
Multivariate Pattern ◽  
Stable Feature

AbstractHow does the human brain encode semantic information about objects? This paper reconciles two seemingly contradictory views. The first proposes that local neural populations independently encode semantic features; the second, that semantic representations arise as a dynamic distributed code that changes radically with stimulus processing. Combining simulations with a well-known neural network model of semantic memory, multivariate pattern classification, and human electrocorticography, we find that both views are partially correct: semantic information is distributed across ventral temporal cortex in a dynamic code that possesses stable feature-like elements in posterior regions but with elements that change rapidly and nonlinearly in anterior regions. This pattern is consistent with the view that anterior temporal lobes serve as a deep cross-modal “hub” in an interactive semantic network, and more generally suggests that tertiary association cortices may adopt dynamic distributed codes difficult to detect with common brain imaging methods.

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