Reference Algorithm of Text Categorization Based on Fuzzy Cognitive Maps

Zhang, Guiyun; Liu, Yang; Zhang, Weijuan; Wang, Yuan‐Yuan

doi:10.1007/978-0-387-44641-7_57

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Cognitive maps are highly complex, and research has developed computational models that can systematically analyze the large number of beliefs and inferences contained by them (Bonham & Shapiro in Axelrod, 1976;Carvalho, 2010;Dornschneider & Henderson, 2016;Elsawah et al, 2015;Guiyun et al, 2006). Nevertheless, to date, there is no standard method that systematically traces the key beliefs and inferences antecedent to decisions contained by cognitive maps.…”

Section: Cognitive Mappingmentioning

confidence: 99%

High‐Stakes Decision‐Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring

Dornschneider

2019

Cognitive Science

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People experiencing similar conditions may make different decisions, and their belief systems provide insight about these differences. An example of high‐stakes decision‐making within a complex social context is the Arab Spring, in which large numbers of people decided to protest and even larger numbers decided to stay at home. This study uses qualitative analyses of interview narratives and social media addressing individual decisions to develop a computational model tracing the cognitive decision‐making process. The model builds on work by Abelson and Carroll (1965), Schank and Abelson (1977), and Axelrod (1976) to systematically trace the inferences connecting beliefs to decisions. The findings show that protest decisions were often based on positive emotions such as pride, hope, courage, and solidarity, triggered by beliefs about successful protest and self‐sacrifice. By contrast, decisions to stay at home were triggered by beliefs about safety, state approval, and living conditions. As one participant said, “When I heard about the revolution in Tunisia, my heart was filled with solidarity for the people.” In the words of a non‐participant: “When people are killed, we must be careful. There are more important things than protest: safety and stability.” This study of individual explanations about events identifies the role of emotions in high‐stakes decision‐making within complex social environments.

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Section: Cognitive Mappingmentioning

confidence: 99%

High‐Stakes Decision‐Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring

Dornschneider

2019

Cognitive Science

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Mining television audience rating based on Fuzzy Cognitive Map

Wang

et al. 2015

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

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The Fuzzy Cognitive Map (FCM) is the product of the combination of fuzzy logic and neural network, and is suitable for the description, prediction and control of the nonlinear system based on dynamic data. The linear regression algorithm is used to obtain the coarse weight matrix model of fuzzy cognitive map, and then a training weight algorithm is used to refine the coarse weight matrix model. The fuzzy cognitive map model is applied to mine the television audience rating, realizing and prediction television playback volume. The experimental result shows that the modeling method is effective

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A New FCM Classifier Model Based on KDTICM

Li¹

2013

J. Inf. Comput. Sci.

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Reference Algorithm of Text Categorization Based on Fuzzy Cognitive Maps

Cited by 3 publications

References 2 publications

High‐Stakes Decision‐Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring

High‐Stakes Decision‐Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring

Mining television audience rating based on Fuzzy Cognitive Map

A New FCM Classifier Model Based on KDTICM

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