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Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologies

Mucheol Kim*, Junho Kim, Mincheol Shin

School of Computer Science and Engineering, Chung-Ang University, 84, Heukseok-ro, Dongjak-gu, Seoul, Korea

* Corresponding Author: Mucheol Kim,

Intelligent Automation & Soft Computing 2020, 26(1), 141-147.


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.


Cite This Article

M. Kim, J. Kim and M. Shin, "Word embedding based knowledge representation with extracting relationship between scientific terminologies," Intelligent Automation & Soft Computing, vol. 26, no.1, pp. 141–147, 2020.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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