Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologies

被引:11
作者
Kim, Mucheol [1 ]
Kim, Junho [1 ]
Shin, Mincheol [1 ]
机构
[1] Chung Ang Univ, Sch Comp Sci & Engn, 84 Heukseok Ro, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Word Embedding; Text Mining; Web Technology; Big Data; Information Retrieval; MANAGEMENT;
D O I
10.31209/2019.100000135
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:141 / 147
页数:7
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