scholarly journals RELATIVE SUBJECTIFICATION AND A SEMANTIC NETWORK MODEL OF ENGLISH MODAL AUXILIARIES

2000 ◽  
Vol 17 (1) ◽  
pp. 80-109
Author(s):  
YUKI-SHIGE TAMURA
2010 ◽  
Vol 34-35 ◽  
pp. 1865-1869
Author(s):  
Xiao Ying Chen ◽  
Bin He

Product design is a problem-solving activity based on knowledge. This paper is devoted to presenting a systematic knowledge representation method of principle solution based on semantic network model. For the expression of product knowledge, the semantic object, constraints and their relationships among the expression of the semantic object network model are proposed step by step. Then the principle solution representation model based on semantic network model is put forwards. The knowledge representation of a car is given as an example, which demonstrates that this method is obviously helpful for knowledge-based design system and product innovation.


Radiotekhnika ◽  
2021 ◽  
pp. 80-92
Author(s):  
M. Yermoshyn ◽  
A. Poberezhnyi ◽  
O. Onopriyenko ◽  
M. Shuryha

The article examines the architecture of a networked knowledge base and the organizational structure of a complex military-purpose system, which is built when a group of troops (forces) is created and kept in a state where it is capable of solving the tasks assigned to it. This requires a deep study of issues not only of modern tactics regarding the preparation and conduct of hostilities, but also more complex issues of scientific substantiation of the architecture of a networked knowledge base and the structure of a complex military system with a networked knowledge base. The internal representation of knowledge in the knowledge base (formal programmatic and logical content) is advisable to implement in the form of an adjacency matrix, which displays the relationship and relationship between target settings; initial conditions; the resources of the grouping of troops (temporary, material, combat and quantitative composition), their costs and replenishment; rules for the use of resources and the choice of criteria for their distribution. The knowledge base synthesizes a mathematical network model for making decisions, which provides a change (correction) of the structure of target attitudes when replenishing the knowledge base. Tasks solved in the knowledge base: selection of vertices and relations when replenishing catalogs; making changes to the adjacency matrix in accordance with the identified or changed relationships between targets. A necessary element of the synthesis of a mathematical network model for making decisions on the preparation and conduct of hostilities is the construction of the structure of the target systems of the system for a specific situation. A feature of controlling the correctness of knowledge presented in the form of target attitudes is the need for a joint analysis of the entire set of target attitudes and initial conditions in their relationship. For this, the matrix of the relations of target attitudes and the matrix of the relations of initial conditions are combined. The control of the correctness of the knowledge base is carried out when replenishing the knowledge base, it includes: identification of contradictions in the structure of target attitudes when making changes to this structure; search and detection of contradictions in the graph of the semantic network according to available resources and time; checking the completeness of the graph of the mathematical network model; issuance of revealed contradictions to an expert and their elimination. A practical approach to building the architecture of a networked knowledge base and the organizational structure of a complex military system can be implemented during the substantiation of the components and elements of the system when creating a grouping of troops (forces).


1977 ◽  
Author(s):  
ΝΙΚΟΛΑΟΣ ΡΟΥΣΣΟΠΟΥΛΟΣ

2016 ◽  
Vol 28 (3) ◽  
pp. 268-274 ◽  
Author(s):  
Feng Yu ◽  
Theodore Peng ◽  
Kaiping Peng ◽  
Sam Xianjun Zheng ◽  
Zhiyuan Liu

Doklady BGUIR ◽  
2020 ◽  
Vol 18 (4) ◽  
pp. 44-52
Author(s):  
V. V. Potaraev ◽  
L. V. Serebryanaya

Semantic network model for representing data and knowledge was analysed. Selection of this model for working with text information was justified. The objective of automatic semantic network generation based on an arbitrary Russian-language text was formulated. Initial data, conditions and constraints necessary for network generation algorithm are listed. As a result of the part-of-speech analysis for each word and word order in a sentence, semantic relations between words are determined. The Lexeme dictionary was created to determine the part of speech of words in sentences. A set of question types used in the semantic network was selected. The number of relations in the network is regulated due to the possibility to use only necessary relation types when resolving a specific task. With that, the relations in semantic network can have very different types, which makes it a universal model for representing data and knowledge. The algorithm was developed which allows one to get answers for the questions asked. The semantic network model was generated automatically for the sentences considered. In the proposed algorithm the semantic network is interpreted as unoriented graph on which breadth-first search algorithm is used to find an answer. The proposed algorithms were implemented in a software tool which automatically generates the semantic network for an arbitrary text. The created software tool allows asking questions and getting answers to them based on the information which is stored in the semantic network. The experiments have shown that the generated semantic network gives correct answers to the questions posed. The network is modified by adding and removing information in it. There is a possibility to choose complexity of network structure depending on a specific task being resolved. The proposed approach for building and working with the semantic network allows one to process texts in various languages, to use it in information systems with natural-language interface, and to resolve such tasks as text classification and text search.


2005 ◽  
Vol 16 (4-5) ◽  
pp. 515-525 ◽  
Author(s):  
Virgilio López-Morales ◽  
Omar López-Ortega

2018 ◽  
Vol 26 (5) ◽  
pp. 1481-1492 ◽  
Author(s):  
Sunghoon Lim ◽  
Conrad S. Tucker ◽  
Kathryn Jablokow ◽  
Bart Pursel

2021 ◽  
Vol 14 (1) ◽  
pp. 122-134
Author(s):  
M. Bangura

Modern models of figurative language processing postulate that figurative expressions (FE), e.g. metaphors, are processed through inclusion of one FE component to the category of another. However, some FE can simply be understood by finding commonalities between FE components. This way of processing is better explained by the early semantic network model, on which modern models of figurative language processing are based. The current study attempts to reveal capabilities of categorization approach and semantic network model to explain mechanisms of different FE processing. Subjects (N=67) performed semantic decision tasks, which required answering the question whether the meaning of the presented adjective corresponds to the meaning of an adjective in the context of an expression presented earlier. The results of reaction time analysis suggest that categorization approach is not exhaustive for the explanation of figurative language processing and some of the effects might be explained in terms of the semantic network model. This indicates that it is necessary to include some semantic network model postulates into modern approaches of figurative language comprehension.


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