From Deep Learning to Deep University : Cognitive Development of Intelligent Systems
Golovianko, M., Gryshko, S., & Terziyan, V. (2018). From Deep Learning to Deep University : Cognitive Development of Intelligent Systems. In J. Szymański, & Y. Velegrakis (Eds.), Semantic Keyword-Based Search on Structured Data Sources. IKC 2017 (pp. 80-85). Lecture Notes in Computer Science, 10546. Springer. doi:10.1007/978-3-319-74497-1_8
Published inLecture Notes in Computer Science;10546
© Springer International Publishing AG, part of Springer Nature 2018. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
Search is not only an instrument to find intended information. Ability to search is a basic cognitive skill helping people to explore the world. It is largely based on personal intuition and creativity. However, due to the emerged big data challenge, people require new forms of training to develop or improve this ability. Current developments within Cognitive Computing and Deep Learning enable artificial systems to learn and gain human-like cognitive abilities. This means that the skill how to search efficiently and creatively within huge data spaces becomes one of the most important ones for the cognitive systems aiming at autonomy. This skill cannot be pre-programmed, it requires learning. We offer to use the collective search expertise to train creative association-driven navigation across heterogeneous information spaces. We argue that artificial cognitive systems, as well as humans, need special environments, like universities, to train skills of autonomy and creativity. ...