@Article{2019.100000135,
AUTHOR = {Mucheol Kim, Junho Kim, Mincheol Shin},
TITLE = {Word Embedding Based Knowledge Representation with Extracting  Relationship Between Scientific Terminologies},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {1},
PAGES = {141--147},
URL = {http://www.techscience.com/iasc/v26n1/39850},
ISSN = {2326-005X},
ABSTRACT = {With the trends of big data era, many people want to acquire the reliable and 
refined information from web environments. However, it is difficult to find 
appropriate information because the volume and complexity of web information 
is increasing rapidly. So many researchers are focused on text mining and 
personalized recommendation for extracting users’ interests. The proposed 
approach extracted semantic relationship between scientific terminologies with 
word embedding approach. We aggregated science data in BT for supporting 
users’ wellness. In our experiments, query expansion is performed with 
relationship between scientific terminologies with user’s intention.},
DOI = {10.31209/2019.100000135}
}