@article{Park_Park_Kang_2018, title={PegasusN: A Scalable and Versatile Graph Mining System}, volume={32}, url={https://ojs.aaai.org/index.php/AAAI/article/view/11372}, DOI={10.1609/aaai.v32i1.11372}, abstractNote={ <p> How can we find patterns and anomalies in peta-scale graphs? Even recently proposed graph mining systems fail in processing peta-scale graphs. In this work, we propose PegasusN, a scalable and versatile graph mining system that runs on Hadoop and Spark. To handle enormous graphs, PegasusN provides and seamlessly integrates efficient algorithms for various graph mining operations: graph structure analyses, subgraph enumeration, graph generation, and graph visualization. PegasusN quickly processes extra-large graphs that other systems cannot handle. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Park, Ha-Myung and Park, Chiwan and Kang, U}, year={2018}, month={Apr.} }