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Fuzzy Cognitive Maps for Analyzing User Satisfaction in Information Services.

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Title: Fuzzy Cognitive Maps for Analyzing User Satisfaction in Information Services.
Authors: Girija, D. K.1 girijadk16@gmail.com, N., Yogeesh2 yogeesh.r@gmail.com, M., Rashmi3
Source: Library of Progress-Library Science, Information Technology & Computer. Jul-Dec2024, Vol. 44 Issue 3, p14425-14432. 8p.
Subject Terms: *Machine learning, *Cognitive maps (Psychology), Satisfaction, Quality of service
Abstract: In this paper, we develop a Fuzzy Cognitive Map (FCM)-based framework for investigating user satisfaction in information services and further focus on how various affecting factors are connected to the overall user service experience. Conventional approaches usually perform poorly with extensive uncertainties or difficult, complex relationships between service quality, response time, usability and personalization. As a case in point, FCMs give us an appropriate mathematical framework to model causal relationships and simulate dynamic interplays between these factors. In the study, critical factors are taken as nodes in FCM and then it establishes causal weights between these so that their importance can be quantified. The state of every concept is then updated via matrix-vector operation and iterative updates with sigmoid activation function until convergence. A comprehensive case study illustrates an actual usage of the FCM framework, and highlights its ability to isolate key drivers that impact satisfaction and suggests avenues for improvement. Next steps include integrating IoT sensors for real-time monitoring, hybrid models with machine learning to improve predictions and relevant applications in different fields which goes from e-commerce to healthcare. This experimentation underscores FCMs potential in decision-making procedures which presents good insight towards enhancing users experience when dealing with information service. [ABSTRACT FROM AUTHOR]
Copyright of Library of Progress-Library Science, Information Technology & Computer is the property of A.K. Sharma, Editor & Publisher and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: In this paper, we develop a Fuzzy Cognitive Map (FCM)-based framework for investigating user satisfaction in information services and further focus on how various affecting factors are connected to the overall user service experience. Conventional approaches usually perform poorly with extensive uncertainties or difficult, complex relationships between service quality, response time, usability and personalization. As a case in point, FCMs give us an appropriate mathematical framework to model causal relationships and simulate dynamic interplays between these factors. In the study, critical factors are taken as nodes in FCM and then it establishes causal weights between these so that their importance can be quantified. The state of every concept is then updated via matrix-vector operation and iterative updates with sigmoid activation function until convergence. A comprehensive case study illustrates an actual usage of the FCM framework, and highlights its ability to isolate key drivers that impact satisfaction and suggests avenues for improvement. Next steps include integrating IoT sensors for real-time monitoring, hybrid models with machine learning to improve predictions and relevant applications in different fields which goes from e-commerce to healthcare. This experimentation underscores FCMs potential in decision-making procedures which presents good insight towards enhancing users experience when dealing with information service. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Library of Progress-Library Science, Information Technology & Computer is the property of A.K. Sharma, Editor & Publisher and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        Type: general
      – SubjectFull: Cognitive maps (Psychology)
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      – SubjectFull: Satisfaction
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              Text: Jul-Dec2024
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