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A Graph-Based Approach to Learn Semantic Descriptions of Data Sources
Published on Nov 28, 20134701 Views
Semantic models of data sources and services provide support to automate many tasks such as source discovery, data integration, and service composition, but writing these semantic descriptions by hand
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Chapter list
A Graph-based Approach to Learn Semantic Descriptions of Data Sources00:00
Problem: How to learn semantic descriptions?00:09
First, what is a semantic description?00:16
Semantic Description00:22
Semantic Types01:11
Relationships01:46
Previous approach to learn semantic descriptions02:25
Karma02:26
Refining The Model - 103:35
Refining The Model - 203:56
Refining The Model - 304:08
Our new approach to learn semantic descriptions04:24
Key idea04:37
Approach05:07
Example05:55
Build a Graph from Known Models - 107:00
Build a Graph from Known Models - 208:15
Build a Graph from Known Models - 308:44
Learn Semantic Types (Previous Work)10:37
Generate Candidate Models - 111:02
Generate Candidate Models - 211:53
Generate Candidate Models - 312:11
Generate Candidate Models - 412:28
Generate Candidate Models - 512:35
Generate Candidate Models - 612:47
Generate Candidate Models - 712:48
Generate Candidate Models - 812:56
Generate Candidate Models - 912:59
Rank Source Models13:18
Evaluation13:36
Results - Dataset 114:41
Results - Dataset 215:18
Related Work15:31
Discussion16:37
Future Work17:12