Classification of EGC output and Mental State Transition Network using Self Organizing Map
Classification of EGC output and Mental State Transition Network using Self Organizing Map
复制标题
使用自组织图对 EGC 输出和心理状态转换网络进行分类
DOI：
10.1109/icsmc.2011.6084145
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
T. Ichimura
中科院分区：
文献类型：
--
作者：
Kazuya Mera;T. Ichimura
心理状态转换网络是一个近似于人类心理和心理反应的基本概念，它是由相互联系的心理状态组成的。它可以通过计算情绪生成计算方法来表示从一种情绪状态到另一种情绪状态的过渡。然而，这种方法忽略了大多数情绪，除了情绪具有最强的影响，虽然EGC可以并行计算20情绪的程度。本文研究了EGC对情感的聚类结果与自组织映射对句子与情感关系的聚类结果之间的差异。心理状态根据地图上的一组情绪进行转换。例如，一组情绪在一组过境的心理状态“快乐”，和消极的心理状态是衰弱。
Mental State Transition Network which consists of mental states connected one another is a basic concept of approximating to human psychological and mental responses. It can represent transition from an emotional state to other one with stimulus by calculating Emotion Generating Calculations method. However, this method ignores most of emotions except for an emotion which has the strongest effect although EGC can calculate the degree of 20 emotions in parallel. In this paper, we investigate the discrepancy between the group of emotions by EGC and the clustering results of the relation of sentences and their emotions by Self Organizing Map. Mental state transits based on the group of emotions on the map. For example, a set of emotions in a group transits the mental state “happy,” and negative mental state is enfeebled.
生成没有答案的交互式问题
DOI：
--
发表时间：
2020
期刊：
影响因子：
--
作者：
中西真央;小林哲則;林良彦
通讯作者：
林良彦