Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologiesopen access
- Authors
- Kim, Mucheol; Kim, Junho; Shin, Mincheol
- Issue Date
- Mar-2020
- Publisher
- TSI PRESS
- Keywords
- Word Embedding; Text Mining; Web Technology; Big Data; Information Retrieval
- Citation
- INTELLIGENT AUTOMATION AND SOFT COMPUTING, v.26, no.1, pp 141 - 147
- Pages
- 7
- Journal Title
- INTELLIGENT AUTOMATION AND SOFT COMPUTING
- Volume
- 26
- Number
- 1
- Start Page
- 141
- End Page
- 147
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/38153
- DOI
- 10.31209/2019.100000135
- ISSN
- 1079-8587
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.
- Files in This Item
-
- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.