Surfacing Thematic Universe using Knowledge Mining and Unsupervised Concept Graph

Author(s):  
Abhijeet Kumar ◽  
Vinayak Kulkrani ◽  
Abhishek Pandey ◽  
Ankit Gupta ◽  
Mridul Mishra
Keyword(s):  
2021 ◽  
Vol 1797 (1) ◽  
pp. 012013
Author(s):  
Rohit Shaw ◽  
Madhusmita Mishra ◽  
Amrut Ranjan Jena

2018 ◽  
Vol 9 ◽  
pp. 1-13 ◽  
Author(s):  
Ying Cheng ◽  
Ken Chen ◽  
Hemeng Sun ◽  
Yongping Zhang ◽  
Fei Tao
Keyword(s):  
Big Data ◽  

Author(s):  
Rihab Idoudi ◽  
Karim Saheb Ettabaa ◽  
Basel Solaiman ◽  
Kamel Hamrouni

2006 ◽  
Vol 05 (04) ◽  
pp. 729-738 ◽  
Author(s):  
P. L. YU

We usually use a set of ideas, thinking paradigms and judgment rules, including alternatives, criteria, outcomes, preferences, to make decision. This set, known as actual domain (working knowledge) of habitual domain, will be stabilized over time unless extraordinary events occur. As such, our working knowledge cannot be broad and deep. Inevitably, we could get into decision traps, which lead us to making wrong decision or solving wrong problems. The actual domain is only a small part of our potential domain, the collection of all thoughts, ideas, thinking paradigms, etc. that have ever been encoded in our brain. In this paper, we will describe nine principles for deep knowledge, so that, we could expand and enrich our working knowledge by utilizing the potential domains of ourselves and other participants in the decision making. As a consequence, good ideas for solving challenging decision problems can be obtained or created. These principles are: The deep and down principle, the alternating principle, the contrasting and complementing principle, the revolving and cycling principle, the inner connection principle, the changing and transforming principle, the contradiction principle, the cracking and ripping principle, the void principle.


Sign in / Sign up

Export Citation Format

Share Document