International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
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SEMANTIC NETWORKS IN AI Saba Qayum1, Piyush Kumar Gupta2 1Saba Qayum,
2Piyush Kumar Gupta, Assistant Professor, 3School of Engineering Sciences and Technology, Jamia Hamdard University, New Delhi, India
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Abstract - This paper describes the origins of semantic
Further, the notion of Idea Generation is discussed in this paper, which discusses how inspiration is essential to develop new solution spaces. This notion, in particular, is discussed here, because learning that as of today our understanding of AI has been mimicking human intelligence was to achieve that we have analyzed previous data and applied logical calculation methods to predict problem solutions to human accuracy and to be precise better and more efficient than human ability, but when mimicking human intelligence we miss out some essential aspects of imagination, idea generation, and creativity which vary for every individual. So, to develop ideas many psychological theories have been proposed and many approaches have been developed to implement such human imagination which does not require past information to form new innovative solutions. This is the main aim of the notion of Idea Generation discussed in this paper.
networks and the methods they were first developed for psychological purposes and then adopted by artificial intelligence techniques to analyze textual data in graph format. This will deepen your understanding and further improve the way you extract knowledge. Thus, semantic network analysis further developed its importance in the field of psychology and later found application in artificial technology based on the emergence of semantic networks. Idea generation, visual text analysis, and conceptual design ideas are further developed. Key Words: Semantic Networks, Idea Generation, Semantic Network Analysis, Conceptual Design, Covid-19
1. INTRODUCTION Semantic network analysis is the prominent way to analyze data by building a network of textual data to visualize such data. Where associations on the basis of semantics are carried out to determine links connectively. Some, define semantic networks as the most effective way to analyze the relationship among notions (text subjects/ words). [1] on the other hand, so define it on the basis of associations carried out by semantics. Thus, this can generate two different schools of thought. Thus, further, elaborating on what constitutes a semantic network, we encounter connecting links, object nodes, and link labels (which define the semantics of the connection). Thus, we can say the formation of a semantic network can be interpreted as links based on their respective semantics. Their prominence first arose in the fields of AI and Natural language processing, for the sole reason of info-visualization or for the use of reasoning based on such visualization, where such functions shown by semantic network representation put forward a way to store info in the graphical format. Thus, further such semantic networks when representing subjects (notions/objects/concepts/words) can represent them in circular, elliptical, or some cases rectangular sections, where their connection to each other can be shown by directed links based on their respective semantics. Link-label is also utilized when the graph is constructed to represent the category of relation are connection which also depends on the connection semantics. Sometimes, such networks are also considered associative between the sub-subject and are carried out to form the connectivity.
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Next, the notion of Visual text analysis is discussed, which became an essential analysis for current-day scenarios, due to the growth of textual information, the unstructured data still arises problems when utilized for analysis or to be specific visual analysis. Nowadays, a certain number of text visualizations require models based on the word frequencies found in the test data to generate the relationship between the text objects and further for the representation. Since text/word relationships are revealed by the semantics available in test data. And lastly, the topic of the design process which is carried out conceptually is discussed. Which defines the process of designing notions that in turn deliver the implementation of desired functions. In this field, i. ii.
Behavior, and Function
These are the two important terms to be considered in the design phase. Whereas, there can be still some probability of encountering ambiguities and their resultant confusion over their visualization, which immensely correspond to the research ideas interchangeably. And the design process of synthesis strategies generation. Input/Output flow regarding the action scheme chosen for the meaning behavior based on the visualization based on such discoveries, a refined framework is proposed for conceptual mechanical product design, where a function–decomposition–mapping process is elaborated to demonstrate the necessities and usefulness of the presented work.
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