Title :
Extracting and integrating nutrition related linked data
Author :
Qingliang Miao ; Ruiyu Fang ; Yao Meng
Author_Institution :
Fujitsu R&D Center Co., Ltd., Beijing, China
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.
Keywords :
data integration; data mining; diseases; health care; medical administrative data processing; ontologies (artificial intelligence); CRF-based approach; DBPedia; Diseasome; Linked Open Data; LinkedCT; extended nutritional ontology; health care; medical data extraction; medical data integration; nutrition related linked data integration; Data mining; Diseases; Electronic publishing; Information services; Internet; Joining processes; Labeling; Data Integration; Knowledge Discovery; Linked Data;
Conference_Titel :
Semantic Computing (ICSC), 2015 IEEE International Conference on
Conference_Location :
Anaheim, CA
DOI :
10.1109/ICOSC.2015.7050835