Name
Abstract | ||
|---|---|---|
The development of modern health care and clinical practice increase the need of nutritional and medical data extraction and integration across heterogeneous data sources. It can be useful for researchers and patients if there is a way to extract relevant information and organize it as easily shared and machine-processable linked data. In this paper, we describe an automatic approach that extracts and publishes nutritional linked data including nutritional concepts and relationships extracted from nutritional data sources. Moreover, we link the nutritional data with Linked Open Data. In particular, a CRF-based approach is used to mine food, ingredient, disease entities and their relationships from nutritional text. And then, an extended nutritional ontology is used to organize the extracted data. Finally, we assign semantic links between food, ingredient, disease entities and other equivalent entities in DBPedia, Diseasome and LinkedCT. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICOSC.2015.7050835 | IEEE International Conference on Semantic Computing |
Keywords | Field | DocType |
Knowledge discovery, data integration, linked data | Data science,Data integration,Information system,Health care,Ontology-based data integration,Ontology,Computer science,Linked data,Knowledge extraction,Data extraction | Conference |
Volume | Issue | ISSN |
9 | 3 | 1793-351X |
Citations | PageRank | References |
0 | 0.34 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingliang Miao | 1 | 0 | 0.34 |
| Ruiyu Fang | 2 | 5 | 2.12 |
| Yao Meng | 3 | 0 | 0.34 |