@Article{2019.100000140,
AUTHOR = {Juryon Paik},
TITLE = {Weighted or Non-Weighted Negative Tree Pattern Discovery from SensorRich Environments},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {1},
PAGES = {193--204},
URL = {http://www.techscience.com/iasc/v26n1/39854},
ISSN = {2326-005X},
ABSTRACT = {It seems to be sure that the IoT is one of promising potential topics today. 
Sensors are the one that lead the current IoT revolution. The advances of 
sensor-rich environments produce the massive volume of raw data that is 
enlarging faster than the rate at which it is being handled. JSON is a lightweight 
data-interchange format and preferred for IoT applications. Before JSON, XML 
was de factor standard format for interchanging data. The common point is that 
their structure scheme is the tree. Tree structure provides data exchangeability 
and heterogeneity, which encourages user-flexibilities. Therefore, JSON sensor 
format is an easy to use human readable format for storing and transmitting 
sensor values. However, it is more challenging than ever to discover valuable 
and hidden information from the continuously generated tree-structured data. 
In the paper, we define and suggest an original method to predict and evaluate 
from the tree-structured sensing data.},
DOI = {10.31209/2019.100000140}
}