scholarly journals Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer

2020 ◽  
Author(s):  
Chao Shang ◽  
Sarthak Dash ◽  
Md. Faisal Mahbub Chowdhury ◽  
Nandana Mihindukulasooriya ◽  
Alfio Gliozzo
Keyword(s):  
Knowledge Transfer ◽  
Domain Knowledge ◽  
Cross Domain

scholarly journals Cross-domain Knowledge Discovery based on Knowledge Graph and Patent Mining

2021 ◽  
Vol 1744 (4) ◽  
pp. 042155
Author(s):  
Fan Ye ◽  
Tie Fu ◽  
Lin Gong ◽  
Jun Gao
Keyword(s):  
Knowledge Discovery ◽  
Domain Knowledge ◽  
Knowledge Graph ◽  
Patent Mining ◽  
Cross Domain

scholarly journals Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data

2021 ◽  
Vol 13 (5) ◽  
pp. 124
Author(s):  
Jiseong Son ◽  
Chul-Su Lim ◽  
Hyoung-Seop Shim ◽  
Ji-Sun Kang
Keyword(s):  
Artificial Intelligence ◽  
Domain Knowledge ◽  
Open Data ◽  
Heterogeneous Data ◽  
Big Data Analysis ◽  
Knowledge Graph ◽  
Cross Domain ◽  
Disaster Data ◽  
Knowledge Graphs ◽  
Open Datasets

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.

scholarly journals A Cross-Domain Recommender System With Kernel-Induced Knowledge Transfer for Overlapping Entities

2019 ◽  
Vol 30 (7) ◽  
pp. 1998-2012 ◽  
Author(s):  
Qian Zhang ◽  
Jie Lu ◽  
Dianshuang Wu ◽  
Guangquan Zhang
Keyword(s):  
Knowledge Transfer ◽  
Recommender System ◽  
Cross Domain
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