Ideation Support System with Personalized Knowledge Level Prediction

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS) Pub Date : 2019-10-01 DOI:10.1109/IUCC/DSCI/SmartCNS.2019.00058

Yui Kita, J. Rekimoto

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Abstract

It is known that computers can improve ideation productivity. For example, conventional systems help users to improve ideations by presenting words that are related to the users' conversational topics. However, these systems usually do not consider the users' vocabulary levels and words that the users do not know may be displayed. This can happen quite often when they are discussing something in their non-native language, or sometimes even in their native language as technical terms may need to be explained in detail. Showing too many unknown words could discourage the users from paying attention to the system and the system would become completely useless. In this research, we introduce a method to estimate the users' vocabulary levels during the ideation process by taking advantage of machine learning techniques. We examine the system usability with a user study and discuss design guidelines for an ideation support system.

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个性化知识水平预测的思维支持系统

众所周知，计算机可以提高创造力。例如，传统系统通过呈现与用户会话主题相关的单词来帮助用户改进构思。然而，这些系统通常不会考虑用户的词汇水平，并且可能会显示用户不认识的单词。当他们用他们的非母语讨论一些事情时，这种情况经常发生，有时甚至在他们的母语中，因为技术术语可能需要详细解释。显示太多的未知单词会让用户对系统失去兴趣，系统会变得毫无用处。在这项研究中，我们介绍了一种利用机器学习技术来估计用户在构思过程中的词汇水平的方法。我们通过用户研究来检查系统的可用性，并讨论构思支持系统的设计指南。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)

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