思维平面数据集:基于Cloninger理论的人工智能模型测量人类思维的新数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES
Atra Joudaki , Leyli Mohammad Khanli , Alireza Farnam , Yashar Sarbaz , Jafar Tanha
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引用次数: 0

摘要

今天,我们看到人工智能取得了显著的进步,特别是在自然语言处理、聊天机器人和情感分析方面。使用情感分析技术,聊天机器人可以更好地理解用户所说的话,并产生更有用的答案。聊天机器人对用户所说的话理解得越多,机器和人之间的互动就会越多。为此,我们必须能够为人工智能系统定义超越情感分析的东西。为此,模型必须能够描述和测量思想。为了解决这个问题,我们使用Cloninger的理论创建了一个数据集。在这个理论中,Cloninger创造了一个人类思维及其发展的全球模型,考虑到动物学习能力的进化来衡量思维。由于人类的思想以前没有被测量过,而进行科学工作需要精确的测量,我们提供这个数据集的目标是使人工智能模型能够做到这一点。Cloninger将人类思维分为五个不同的层面。这些层面包括:性(2)、物质(3)、情感(4)、智力(5)和精神(7)。三位专家根据Cloninger的理论,将前1万个常用词典单词标记为这个数据集。然后,我们使用这些标记的单词作为基础真理来标记句子。在这个数据集中,我们已经使用这个理论标记了2万个句子,这样我们就可以使用这个数据集让人工智能模型更加理解用户的语句。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Planes of thought dataset: A new dataset for the measurement of human thought by artificial intelligence model based on Cloninger's theory
Today, we have seen remarkable progress in artificial intelligence, especially in natural language processing, chatbots, and sentiment analysis. Using sentiment analysis techniques, chatbots can better understand what users say and produce more useful answers. The more the chatbot understands what the users say, the more interactions between the machine and human will be created. To this end, we must be able to define beyond sentiment analysis for artificial intelligence systems. For this, models must be able to describe and measurement of thought. To solve this challenge, we have created a dataset using Cloninger's theory. In this theory, Cloninger created a global model of human thought and its development, considering the evolution of animal learning abilities to measure thought. Since the thought of humans has not been measured before and accurate measurement is required to perform scientific work, our goal in providing this dataset is to enable artificial intelligence models to do this. Cloninger has divided human thought into five different planes. These planes include: sexual (2), material (3), emotional (4), intellectual (5), and spiritual (7). Three experts labeled the first 10,000 frequently used dictionary words to collect this dataset using Cloninger's theory. We then used these labeled words as ground truths to label sentences. In this dataset, we have labeled 20,000 sentences using this theory so that we can use this dataset to make artificial intelligence models more understanding of the user’s statements.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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