TY - GEN
T1 - Graph mining meets the Semantic Web
AU - Lee, Sangkeun
AU - Sukumar, Sreenivas R.
AU - Lim, Seung Hwan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/19
Y1 - 2015/6/19
N2 - The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-Algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.
AB - The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-Algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.
UR - https://www.scopus.com/pages/publications/84944325072
U2 - 10.1109/ICDEW.2015.7129544
DO - 10.1109/ICDEW.2015.7129544
M3 - Conference contribution
AN - SCOPUS:84944325072
T3 - Proceedings - International Conference on Data Engineering
SP - 53
EP - 58
BT - ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops
PB - IEEE Computer Society
T2 - 2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015
Y2 - 13 April 2015 through 17 April 2015
ER -